Proceedings of the 30 th Meeting. WORKING GROUP on PROLAMIN ANALYSIS and TOXICITY. Edited by Peter Koehler German Research Centre for Food Chemistry

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1 Proceedings of the 30 th Meeting WORKING GROUP on PROLAMIN ANALYSIS and TOXICITY Edited by Peter Koehler German Research Centre for Food Chemistry September 2016 Valencia, Spain

2 Proceedings of the 30 th Meeting WORKING GROUP on PROLAMIN ANALYSIS and TOXICITY Edited by Peter Koehler Deutsche Forschungsanstalt für Lebensmittelchemie / German Research Centre for Food Chemistry Freising Peter Koehler April 2017

3 Impressum Proceedings of the 30 th Meeting WORKING GROUP on PROLAMIN ANALYSIS and TOXICITY September 2016 Valencia, Spain This work including all parts is subject to copyright. All rights are reserved and any utilisation is only permitted under the provisions of the German Copyright Law. Permissions for use must always be obtained from the publisher. This is in particular valid for reproduction, translation, conversion to microfilm and for storage or processing in electronic systems. Scientific Organisation Prof. Dr. Peter Koehler Deutsche Forschungsanstalt für Lebensmittelchemie Lise-Meitner-Str. 34, FREISING, GERMANY Phone: ; Fax: Host Prof. Dr. Cristina M. Rosell Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino 7, PATERNA, VALENCIA, SPAIN Phone: , Fax: Cover picture * and picture of participants Thomas Mothes Peter Koehler ISBN: * Cover picture: Sculptural set called Solar system in blue which is situated in the inner court of the Institute of Agrochemistry and Food Technology (IATA-CSIC). The set is formed by a telescope and a schematic representation of our solar system.

4 Preface In October 2014, I asked Cristina Rosell if she would be willing to host the 30 th meeting of the Working Group on Prolamin Analysis and Toxicity (PWG) and she accepted with pleasure. She learned about the PWG meeting as a guest at the 2015 meeting in Tulln, Austria and started planning her own meeting. Together with her colleague Maria Saneustaquio she organised the PWG meeting 2016 at the Hotel Sercotel Sorolla Palace, Valencia, Spain from 22 to 24 September Cristina and Maria were present during the entire meeting. As the chairman of the PWG, I assume that going to Valencia at this weekend was like returning into summer. The PWG was hosted by the Institute of Agrochemistry and Food Technology (IATA-CSIC) and the Asociacón de Celíacos de la Communidad Valenciana. The PWG, the invited speakers, the participants from industry (cereal starch producers, producers of glutenfree food, producers of kits for gluten analysis) and research institutes as well as the delegates from European coeliac societies came together and had very interesting oneand-a-half days of presentations, discussions and networking. Analytical and clinical work in the field of coeliac disease and gluten done in the labs of the PWG members as well as results of guests and invited speakers were presented in 22 talks and intensely discussed at the meeting. In addition, one presentation was focussed on regulatory aspects of gluten analysis and labelling. This was the highest number of presentations at the PWG meeting during the last decade. A symposium on Enzymatic Gluten Degradation with two presentations of internationally recognised experts highlighted the latest advances in the field of gluten-specific peptidases. I would like to express my thanks to all participants of the meeting for their active contributions and the discussions that resulted thereof. I am in particular grateful to Maria Saneustaquio and Cristina Rosell from IATA-CSIC for their enthusiasm and hospitality, which made this perfectly organised meeting a great success. Also, very special thanks to Katharina Scherf for her invaluable help in proofreading. Finally, I would like to express my appreciation to all friends, colleagues and sponsors for their ongoing support of the PWG and the meeting. Freising, March 2017 Peter Koehler

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6 Table of contents 5 Table of Contents 1 Executive Summary List of Participants Programme Analytical research reports Alternatives for developing gluten-free bakery foods Cristina M. Rosell 4.2 Detection of gluten in products containing barley: A proposal for C-hordein as reference material Xin Huang, Päivi Kanerva, Hannu Salovaara, Tuula Sontag-Strohm 4.3 Quantitation of the 33-mer peptide from α-gliadins in wheat flours by LC-MS/MS Kathrin Schalk, Christina Lang, Herbert Wieser, Peter Koehler, Katharina A. Scherf 4.4 The gluten content of wheat starches Tanja Šuligoj, H. Julia Ellis, Paul J. Ciclitira 4.5 Comparison of immunomethods for the characterization of gluten immunogenic peptides in a commercial beer Alba Muñoz-Suano, Miguel Ángel Síglez, Isabel Comino, Lourdes Moreno, Ana Real, Carolina Sousa, María Isabel Torres, Elena Quesada-Hernández, Ángel Cebolla 4.6 Pathogenesis of coeliac disease: complexes between transglutaminase and gluten peptides Barbara Lexhaller, Peter Koehler, Katharina Scherf 4.7 Potential of non-prolamin storage proteins in coeliac disease Gyöngyvér Gell, Gábor Veres, Ilma Rita Korponay-Szabó, Angéla Juhász

7 6 Table of contents 4.8 Preview of the Well on Wheat? (WoW) project Twan AHP America, Luud JWJ Gilissen, Marinus JM Smulders, Peter Shewry, Flip van Straaten, Daisy Jonkers, Fred Brouns 5 Clinical research reports Oats in the diet of children with coeliac disease: a double-blind, randomised, placebo-controlled multicenter study Tiziana Galeazzi, Simona Gatti Caporelli Nicole, Elena Lionetti, Ruggero Francavilla, Maria Barbato, Paola Roggero, Basilio Malamisura, Giuseppe Iacono, Andrea Budelli, Rosaria Gesuita, Carlo Catassi1 5.2 A study of morphological and immunological responses to a 14 day gluten challenge in adults with treated coeliac disease Vikas K. Sarna, Gry I. Skodje, Henrik M. Reims, Louise F. Risnes, Shiva D. Koirala, Ludvig M. Sollid, Knut E.A. Lundin 5.3 A double-blind placebo-controlled cross-over challenge with gluten and fructans in individuals with self-reported gluten sensitivity Gry I. Skodje, Vikas K. Sarna, Ingunn H. Minelle, Kjersti L. Rolfsen, Jane G Muir, Peter R. Gibson, Marit B. Veierød, Christine Henriksen, Knut EA. Lundin 5.4 Natural history and management of potential coeliac disease Renata Auricchio, Valentina Discepolo, Roberta Mandile, Maria Maglio, Luigi Greco, Riccardo Troncone 5.5 Association between IL-33/ST2 axis and active coeliac disease Federico Perez, David Diaz Jimenez, Carolina N. Ruera, Marjorie de la Fuente, Glauben Landskron, Agustina Redondo, Luciana Guzman, Marcela Hermoso, Fernando Chirdo

8 Table of contents Abrogation of coeliac immunogenicity of gluten peptides by amino acid point substitutions Nika Japelj, Beatriz Côrtez-Real, Tanja Šuligoj, Wei Zhang, Joachim Messing, Uma Selvarajah1, Paul J. Ciclitira 5.7 Estimation of (sero) prevalence of coeliac disease in children and adolescents in the LIFE Child study cohort Johannes Wolf, Norman Haendel, Anne Jurkutat, Carl Elias Kutzner, Gunter Flemming, Wieland Kiess, Andreas Hiemisch, Antje Körner, Wolfgang Schlumberger, Joachim Thiery, Thomas Mothes 5.8 Results of the prospective multicentre trial of antibody diagnostics in coeliac disease (AbCD) Johannes Wolf, David Petroff, Dirk Hasenclever, Thomas Mothes 6 Enzymatic gluten degradation Identification of novel and food-grade gluten-degrading enzymes Eva J. Helmerhorst, Guoxian Wei, Na Tian, Detlef Schuppan 6.2 Studying kinetics of intestinal gluten degradation using peptide libraries Niels Röckendorf, Andreas Frey 7 Statements on current developments concerning gluten analysis, clinical and legal aspects News from Codex and regulatory affairs Hertha Deutsch 7.2 Considerations concerning methods for gluten quantitation in foods (R5/G12 ELISA) Peter Koehler, Fernando Chirdo, Hertha Deutsch, Thomas Mothes, Olivier Tranquet, Katharina Scherf 8 Perspectives and action plan of the PWG Peter Koehler

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10 1 Executive Summary 9 1 Executive summary Among the topics of the meeting were food technological aspects of the production of gluten-free baked goods, the importance of the small intestinal microbiome in the diet of coeliac disease patients, analytical issues of gluten, clinical studies on coeliac disease and non-celiac gluten sensitivity, serology of coeliac disease, further aspects of the pathomechanism of coeliac disease, as well as legal issues. Analytical session Six presentations were given in this session. A novel reference material for barley gluten based on C-hordeins was suggested. It appears that the immunodominant 33- mer peptide is common among wheat cultivars but without being correlated with the gluten content. Data on problems in the quantitation of the gluten content of wheat starches induced lively discussions, which are also related to the future evaluation of ELISA methods for approval with the Codex Alimentarius. This led to a meeting of experts after the end of the conference to discuss about further actions. Finally, breeding activities for wheat without coeliac disease activity and a possible role of non-gluten proteins in coeliac disease were on the agenda. Clinical session This session included twelve presentations, which was by far the highest number during the last years. Topics were widespread and included in vivo studies with different diets in coeliac disease and non-celiac gluten sensitivity. Serological studies showed that blood tests are now of major importance in the diagnosis of coeliac disease. The issue of partially hydrolysed gluten for the immune system was highlighted as well as the impact of amylase-trypsin inhibitors on intestinal inflammations. Crystallographic studies on the interaction between HLA-DQ-gluten and gluten-specific T-cell receptors gave insights into the pathomechanism of coeliac disease. Symposium: Enzymatic gluten degradation The symposium comprised two presentations on the identification and use of enzymes for degrading gluten and gluten peptides. A very interesting talk described the identification of gluten-specific peptidases of the subtilisin family from dental plaque. Some of these enzymes have a food-grade status and are promising candidates for preparations that could be used for gluten detoxification of foods or as oral supplements for gluten degradation in the stomach. The second presentation dealt with the application of peptide libraries to determine the stability of gluten peptides towards gastrointestinal peptidases. Rat enzymes have been used so far, but the approach is promising for the human peptidase system.

11 30 th Meeting of the Working Group on Prolamin Analysis and Toxicity (PWG), Valencia, Spain, September 2016

12 2 List of Participants 11 2 List of Participants GROUP MEMBERS Prof. Dr. Fernando G. Chirdo Universidad Nacional de La Plata Facultad de Ciencias Exactas Instituto de Estudios Immunologicos y Fisiopatologicos - IIFP Calle 47 y 115 (1900) LA PLATA, ARGENTINA Phone: (Int 45) Fax: fchirdo@biol.unlp.edu.ar Prof. Dr. Paul J. Ciclitira GSTT NHS Trust Curve Business Hub, Unit 1 30B Wilds Rents LONDON SE1 4QG UNITED KINGDOM Phone: pjcgastro@gmail.com Prof. Dr. Carlo Catassi (not attending), substituted by Dr. Tiziana Galeazzi Università Politecnica delle Marche Facoltà di Medicina e Chirurgia Istituto di Clinica Pediatrica Via Corridoni ANCONA, ITALY Phone: Fax: t.galeazzi@univpm.it Prof. Dr. Peter Koehler Deutsche Forschungsanstalt für Lebensmittelchemie Lise-Meitner-Straße FREISING, GERMANY Phone: Fax: peter.koehler@tum.de Prof. Dr. Frits Koning Leiden University Medical Centre, E3-Q Department of Immunohaematology and Bloodbank Albinusdreef ZA LEIDEN, THE NETHERLANDS Phone: Fax: fkoning@lumc.nl Prof. Dr. Knut Lundin Oslo Universitetssykehus HF Rikshospitalet Postboks 495 N-0424 OSLO, NORWAY Phone: Fax: k.e.a.lundin@medisin.uio.no Prof. Dr. Thomas Mothes Universitätsklinikum Leipzig A.ö.R. Institut für Laboratoriumsmedizin, Klinische Chemie und Molekulare Diagnostik Liebigstraße LEIPZIG, GERMANY Phone: Fax: mothes@medizin.uni-leipzig.de Dr. René Smulders Plant Research International (PRI) Wageningen University Droevendaalsesteeg PB WAGENINGEN, THE NETHERLANDS Phone: rene.smulders@wur.nl

13 12 2 List of Participants Dr. Olivier Tranquet INRA Rue de la Géraudière BP NANTES CEDEX 3, FRANCE Phone: Fax: olivier.tranquet@nantes.inra.fr Prof. Dr. Riccardo Troncone Department of Pediatrics and European Laboratory for the Investigation of Food-Induced Diseases University of Naples Federico II Via Pansini, NAPLES, ITALY Phone: Fax: troncone@unina.it Prof. Dr. Detlef Schuppan (not attending), substituted by Dr. Victor Zevallos I. Medizinische Klinik und Poliklinik Universitätsmedizin der Johannes Gutenberg-Universität Mainz Institut für Translationale Medizin Obere Zahlbacher Str MAINZ, GERMANY Phone: Fax: zevallos@uni-mainz.de HOSTS Prof. Dr. Cristina Molina Rosell Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN Phone: Fax : crosell@iata.csic.es Ms. Maria Vicenta San Eustaquio Tarazona Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN Phone: Fax : marivise@iata.csic.es INVITED SPEAKERS Dr. Andreas Frey Forschungszentrum Borstel Leibniz-Zentrum für Medizin und Biowissenschaften Parkallee BORSTEL, GERMANY Phone: Fax: +49 (0) afrey@fz-borstel.de Dr. Eva Helmerhorst Boston University Department of Molecular and Cell Biology 700 Albany Street BOSTON, MA USA helmer@bu.edu Prof. Dr. Yolanda Sanz Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN yolsanz@iata.csic.es

14 2 List of Participants 13 GUESTS Mrs. Tova Almlöf Semper AB Semper AB Box 1101 SE SUNDBYBERG, SWEDEN Phone : tova.almlof@semper.se Mrs. Sofia Beisel Deutsche Zöliakiegesellschaft e.v. Kupferstr STUTTGART, GERMANY Phone: Fax: sofia.beisel@dzg-online.de Dr. Markus Brandt Ernst Böcker GmbH & Co KG Ringstrasse MINDEN, GERMANY Phone: Fax: markus.brandt@sauerteig.de Dr. Maria Angeles Bustamente Universidad del Pais Vasco Euskal Herrika Unibertsitatea Universität des Baskenlandes / EHU Barrio Sarriena s/n Neighborhood Sarriena s / n LEIOA; BIZKAIA, SPAIN marian.bustamente@ehu.eus Dr. Angel Cebolla-Ramirez Biomedal, SL Avenida Américo Vespucio, Geschoss 1, Modul 12, SEVILLA, SPAIN Phone: Fax: acebolla@biomedal.com Mr. Henrik Dahlquist Fria Gluten Free Fältspatsgatan VÄSTRA FRÖLUNDA, SWEDEN Phone: henrik.dahlquist@fria.se Dr. Johan De Meester Cargill R&D Centre Europe Havenstraat 84 B-1800 VILVOORDE, BELGIUM Phone: Johan_De_Meester@cargill.com Mrs. Hertha Deutsch Österreichische Arbeitsgemeinschaft Zöliakie Anton Baumgartner Straße 44/C5/ VIENNA, AUSTRIA Phone: hertha.deutsch@chello.at Mrs. Angela Durá de Miguel Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN andudemi@iata.csic.es Mr. Richard Fielder Bio-Check (UK) Spectrum House, Llys Edmund Prys, St. Asaph Business Park LL17 0JA ST. ASAPH, UK Phone: Fax: richard@biocheck.uk.com

15 14 2 List of Participants Mrs. Raquel Garzón Lloria Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN r.garzon@iata.csic.es Mrs. Anna Gibert Casamada Associació Celíacs de Catalunya Independencia, BARCELONA, SPAIN annagibertc@gmail.com Ms. Eugenia Yaiza Benavent Gil Institute of Agrochemistry and Food Technology (IATA-CSIC) Avenida Agustin Escardino PATERNA, VALENCIA, SPAIN yaizabenavent@gmail.com Dr. Gyöngyvér Gell MTA Centre of Agricultural Research Department of Applied Genomics Brunszvik MARTONVÁSÁR, HUNGARY Phone: Fax: gell.gyongyver@agrar.mta.hu Mr. Phil Goodwin Bio-Check (UK) Spectrum House, Llys Edmund Prys, St. Asaph Business Park LL17 0JA ST. ASAPH, UK Phone: Fax: phil@biocheck.uk.com Dr. Thomas Grace Bia Diagnostics 480 Hercules Dr COLCHESTER, VT, USA Phone: thomasgrace@biadiagnostics.com Mr. Daniele Grano Dr. Schär AG /SPA Winkelau BURGSTALL, ITALY Daniele.Grano@drschaer.com Mrs. Mia Hallgren Swedish Food Agency P.O. Box 622 SE UPPSALA, SWEDEN mia.hallgren@slv.se Mrs. Katri Hautanen Fria Gluten Free Fältspatsgatan VÄSTRA FRÖLUNDA, SWEDEN Phone: katri.hautanen@fria.se Mr. Xin Huang University of Helsinki Department of Food and Environmental Sciences Agnes Sjöbergin katu 2, PL66 14 HELSINKI, FINLAND Phone: xin.huang@helsinki.fi Mrs. Jasmin Kraus Romer Labs Division Holding GmbH Erber Campus GETZERSDORF, AUSTRIA Phone: jasmin.kraus@romerlabs.com Dr. Götz Kröner Hermann Kröner GmbH Lengericher Str IBBENBÜREN, GERMANY Phone: Fax: kroener@kroener-staerke.de

16 2 List of Participants 15 Mrs. Barbara Lexhaller Deutsche Forschungsanstalt für Lebensmittelchemie Lise-Meitner-Str FREISING, GERMANY Phone: Mrs. Stelle Lindeke R-Biopharm AG An der neuen Bergstraße DARMSTADT, GERMANY Phone: Dr. Maria Carmen Mena Valverde National Center of Biotechnology, CSIC MADRID, SPAIN Phone: Fax: Dr. Luisa Novelino Fondazione Celiachia Via Caffaro, GENOVA, ITALY Phone: Mrs. Ombretta Polenghi Dr. Schär R&D Centre c/o AREA Science Park Padriciano, 99 I TRIESTE, ITALY Phone: Dr. Elena Quesada Hernández Biomedal, SL Avenida Américo Vespucio, Geschoss 1, Modul 12, SEVILLA, SPAIN Mrs. Catherine Remillieux-Rast Association Française des Intolérants au Gluten (AFDIAG) 23 Rue de Venise VAUX-SUR-SEINE, FRANCE Phone: Fax: Dr. Adrian Rogers Romer Labs UK Ltd. The Health Business and Technical Park WA74QX RUNCORN, CHESHIRE, UK Phone: Dr. Cristina Romero INGENASA C/Hermanos García Noblejas, MADRID, SPAIN Phone: Fax: Mr. Nermin Sajic EuroProxima B.V. Beijerinckweg BN ARNHEM, THE NETHERLANDS Phone: Dr. Martin Salden EuroProxima B.V. Beijerinckweg BN ARNHEM, THE NETHERLANDS Phone:

17 16 2 List of Participants Prof. Hannu Salovaara University of Helsinki Department of Food and Environmental Sciences Agnes Sjöbergin katu 2, PL66 14 HELSINKI, FINLAND hannu.salovaara@helsinki.fi Dr. Vikas Kumar Sarna Dep. of Immunology Hospital- Rikshospitalet NORWAY vikas.sarna@medisin.uio.no Dr. Katharina Scherf Deutsche Forschungsanstalt für Lebensmittelchemie Lise Meitner-Strasse FREISING, GERMANY Phone: Fax: katharina.scherf@lrz.tum.de Dr. Juan Ignacio Serrano-Vela Asociacion de Celiacos de Madrid Calle Lanuza 19-bajo MADRID, SPAIN Phone: Fax: nachoserrano@celiacosmadrid.org Dr. Edurne Simón University of the Basque Country UPV/EHU Paseo de la Universidad, VITORIA-GASTEIZ, SPAIN Phone: Fax: edurne.simon@ehu.es Mrs. Gry Skodje Oslo University Hospital OSLO, NORWAY g.i.skodje@gmail.com Dr. Tuula Sontag-Strohm University of Helsinki Agnes Sjöbergin katu , HELSINKI, FINLAND Phone: tuula.sontag-strohm@helsinki.fi Mrs. Pauline Titchener Neogen Europe Ltd. The Dairy School, Auchincruive KA6 5HU AYR, SCOTLAND, UK Phone: Fax: p.titchener@neogeneurope.com Dr. Angel Venteo INGENASA C/Hermanos García Noblejas nº MADRID, SPAIN Phone: Fax: aventeo@ingenasa.com Dr. Paul Wehling Medallion Labs 9000 Plymouth Avenue North, MINNEAPOLIS, MN 55427, U.S.A. Phone: paul.wehling@genmills.com Dr. Thomas Weiss R-Biopharm AG An der neuen Bergstrasse DARMSTADT, GERMANY Phone: t.weiss@r-biopharm.de Mrs. Maren Wiese Hermann Kröner GmbH Lengericher Straße IBBENBÜREN, GERMANY Phone: Fax: wiese@kroener-staerke.de

18 3 Programme 17 3 Programme THURSDAY, 22 September :00 Arrival of Prolamin Working Group and all participants Informal get-together with dinner Welcome by Cristina Rosell Location: Hotel Sercotel Sorolla Palace, Valencia FRIDAY, 23 September :30 Bus transfer to the institute 09:00 Opening of the meeting (Peter Koehler) 09:15 Alternatives for developing gluten-free bakery foods Prof. Dr. Cristina M. Rosell, Valencia, Spain 10:00 Analytical research reports Chirdo, Ciclitira, Feighery, Gilissen, Koehler, Koning, Lundin, Mothes, Schuppan, Tranquet; guests 11:00 Coffee break 11:30 Analytical research reports (continuation) 12:10 Clinical research reports 12:50 Lunch Catassi, Chirdo, Ciclitira, Feighery, Koning, Lundin, Mothes, Schuppan, Troncone; guests 14:00 Clinical research reports (continuation) 16:00 Coffee break 16:30 The Prolamin Working Group Executive Meeting (members only) 17:00 Bus transfer to the hotel 18:15 Bus departure from the hotel for all participants Short reception at the city hall of Valencia Joint dinner: Restaurante Contrapunto, Palau de les Arts, Valencia 23:00 Bus departure to the hotel

19 18 3 Programme SATURDAY, 24 September :30 Bus transfer to the institute 09:00 Interplay between gut microbiota and diet in coeliac disease Yolanda Sanz, Valencia, Spain SYMPOSIUM 09:45 Enzymatic Gluten Degradation Chair: Prof. Dr. Frits Koning, Leiden, The Netherlands 09:50 Identification of Novel and Food-grade Gluten-degrading Enzymes Eva Helmerhorst, Boston, U.S.A. 10:30 Studying Kinetics of Intestinal Gluten Degradation Using Peptide Libraries Dr. Andreas Frey, Borstel, Germany 10:50 Coffee break 11:20 Clinical research reports (continuation) 12:20 Discussion of current developments concerning gluten analysis, clinical and legal aspects 13:00 Lunch Statements by participating organisations, representatives from industry and guests Outline: Action plan 2017 of the Prolamin Working Group 14:00 Bus transfer to the hotel and farewell Afternoon Extra time for informal meeting and additional PWG executive meeting concerning action plan Tour of Valencia and joint dinner in a tapas bar SUNDAY, 25 September 2015 Departure of the Prolamin Working Group

20 4 Analytical research reports 19 4 Analytical research reports 4.1 Alternatives for developing gluten-free bakery foods Cristina M. Rosell Institute of Agrochemistry and Food Technology (IATA-CSIC), Valencia, Spain Introduction Cereals, and more precisely wheat, have been at the base of the food pyramid through the human history. Even today, cereals are the main players feeding human population; although their worldwide contribution to nutrient uptake is different. However, there are specific targeted groups with special requirements when consuming cereals, namely gluten-containing grains. Coeliac disease, first considered to be a gastrointestinal disease, is a gluten-sensitive enteropathy with genetic, immunologic, and environmental bases. Great efforts are being made to understand the gluten-related pathologies from the genetic and immunologic point of view and also the implication of diet and gluten-free products on the life quality of the patients [1]. The clearest statement is that the only way to ameliorate the symptoms is keeping a lifelong diet free of gluten products. In the last decade, gluten-free foods have shifted exponentially from a niche market to become a revolution and to mark a lifestyle. Gluten-free has been described by consumers as: a mainstream sensation, embraced by both out of necessity and as a personal choice toward achieving a healthier way to live. However, in this scenario nutritionists must play a fundamental role conducting counselling and closely following the dietary management of coeliac individuals. The initial challenge when developing gluten-free products as a necessity for solving pathologies was to overcome the technological restrictions that the absence of gluten provoked in the development of fermented cereal-based foods [2]. The main goal was to look for tools to technologically replace the gluten giving sensorially accepted products. However, gluten is not just a great protein matrix, it is a protein with incomparable viscoelastic properties. Because of that its replacement has been an enormous challenge during decades, and it is still a hot topic. Initially, only starches and hydrocolloids were considered but later on, different tools have been developed for defining food recipes resembling the quality of gluten-containing goods. Nevertheless, in this picture not only the sensorial quality must be considered, it is an essential requirement that those gluten-free foods provide the required nutrients intake for those gluten-intolerants, contributing also to their wellbeing and healthy status at present and also considering long-term nutrition.

21 20 Alternatives for developing gluten-free bakery foods Technological approaches for miming gluten in gluten-free bakery products Replacement of gluten functionality has been a challenge for food technologists. Its absence leads to less cohesive and elastic doughs that result in bread with a crumbling texture, poor colour and low specific volume. Therefore, in the last years numerous studies have been focused on improving the physical properties of gluten-free foods, particularly fermented and baked foods like bread [3]. Gluten-free recipes are very complex, and gluten-free bread is the result of the interaction of the ingredients. Generally, bread development without gluten has involved the use of diverse ingredients and additives with the purpose to obtain wheat bread-like properties. Approaches proposed for obtaining gluten-free bread include the use of different naturally gluten-free flours (rice, maize, sorghum, soy, buckwheat) and starches (maize, potato, cassava, rice), dairy ingredients (caseinate, skim milk powder, dry milk, whey), gums and hydrocolloids (guar and xanthan gums, alginate, carrageenan, hydroxypropyl methylcellulose, carboxymethyl cellulose), emulsifiers (DATEM, SSL, lecithins), non-gluten proteins from milk, eggs, legumes and pulses, enzymes (cyclodextrin glycosyltranferases, transglutaminase, proteases, glucose oxidase, laccase), and non-starch polysaccharides (inulin, galactooligosaccharides). Strengthening additives or processing aids have been fundamental for miming gluten Glucose oxidase A B C Protease D E F Figure 1. Cross section of corn breads obtained with different enzymes (glucose oxidase and protease) at different levels (expressed as % (w/w) flour basis). Basic recipe contained 1% xanthan gum. A: Glucose oxidase-0%, B: Glucose oxidase- 0.01%, C: Glucose oxidase-0.02%, D: Protease-0.05%, E: Protease-0.1%, F: Protease-0.2%

22 4 Analytical research reports 21 viscoelastic properties [4]. With that purpose, mainly hydrocolloids have been used for building an internal network able to hold the structure of fermented products. With the same purpose, different crosslinking enzymes such as glucose oxidase, transglutaminase and laccase have been used for obtaining a protein network within the flour proteins [5]. Nevertheless, even the disruption of the flour proteins with proteases has been revealed as a good strategy to improve dough performance and in consequence the features of the resulting breads, owing to the decrease of protein hydrophobicity [5]. However, it must be stressed that the effect of the enzymes as gluten-free processing aids is greatly dependent on the type of flour, enzyme source and level, which could lead to improve the bread performance or even to the opposite effect (Fig. 1). Very often the combinations of ingredients and the optimization of the breadmaking process can overcome the technological problems, yielding gluten-free products that meet the consumer s expectations concerning texture and appearance of the fresh bread [6,7]. Nutritional and health aspects of gluten-free products. Previous reviews showed that much research has been conducted on gluten-free foods from different angles to obtain good quality gluten-free-foods. Nevertheless, the nutritional quality of those products has been of interest only recently. In the last five years, the driving force behind gluten-free research has been the nutritional quality. Very recently, Matos and Rosell [8] reviewed the different available strategies for improving the nutritional quality of gluten-free breads. The absence of gluten in natural and processed foods constitutes the therapy treatment for coeliac disease, which may lead to nutritional consequences linked to the composition of gluten-free products. The exclusion of gluten-containing cereals, important vitamin and mineral sources, from the diet might provoke deficiencies in iron, vitamin B and dietary fibre. In fact, common nutrient deficiencies in coeliac subjects at diagnosis are calory/protein, fibre, iron, calcium, magnesium, vitamin D, zinc, folate, niacin, vitamin B12 and riboflavin [9]. Following a lifelong gluten-free diet requires a parallel nutrition counselling, not only focused on the foods to avoid when sticking to a glutenfree diet, but also the nutritional quality of gluten-free products must enter into the equation to elude deficits and imbalances. Some concerns have arisen after publishing some reports showing that the nutritional quality of gluten-free products available on the market were poorer than their glutencontaining counterparts. Gluten-free breads are starch based foods low in proteins and high in fat content, with high glycaemic index [10]. Therefore, a lifelong adherence to gluten-free products could lead to undernourishment and also mineral deficiencies that might end in anaemia, osteopenia or osteoporosis. In the particular case of gluten intolerance, it must also be considered of that coeliac disease induces an intestinal lesion that leads to various deficiencies of nutrients, vitamins, and dietary minerals, with ferropenia, vitamin B12, folic acid, and fat-soluble vitamin deficiencies being especially frequent.

23 22 Alternatives for developing gluten-free bakery foods Therefore, a careful design of gluten-free bakery goods is needed for obtaining glutenfree baked products resembling the nutritional composition of their gluten counterparts to meet dietary guidelines without changing their dietary pattern and to avoid nutrient deficiencies. Enrichment or fortification is a strategy commonly applied to mitigate nutritional deficiencies of the population and wheat flour has been a common carrier for minerals and vitamins. In the case of gluten-free products, although this strategy has been less exploited, there are some trends to complement or balance the nutritional composition of those foods. In the case of minerals calcium salts like lactate, citrate, chloride and carbonate have been proposed as sources of elementary calcium for obtaining fortified gluten-free breads [11]. The supplementation of gluten-free bread with proteins has been a technological strategy for improving the protein network and also for increasing the nutritional quality of gluten-free breads. Legume flours have become very useful for protein and fibre enrichment of bakery foodstuff, like gluten-free cakes, although it is necessary to carefully select the legume to avoid any effect on the technological and sensorial quality [12]. Lately, the physical treatment of the raw materials for enhancing the nutritional quality or healthy pattern is gaining popularity. The selection of the particle size distribution in the gluten-free flours has great impact on the technological properties of the products, but it also determines the glycaemic index of the resulting fresh products. For instance, in rice flour, particle size heterogeneity is responsible or different patterns in starch enzymatic hydrolysis, allowing the modulation of their digestibility. Particularly, enzymatic digestibility increases with the reduction of the particle size [13]. With the same purpose, germination, toasting or cooking of the grains have been proposed for increasing the nutritional, functional, and sensory properties of grains such as pulses and cereals [14-15]. For instance germination of rice kernels under controlled conditions of temperature and time allows the degradation of beta-glucans, increases the content of certain essential amino acids and B-group vitamins and improves protein and starch digestibility. Further research Currently, research is moving fast and numerous gluten-free foods are launched annually. In spite of scientific advances, there is no date in the near future for having high quality gluten-free food products nutritionally equivalent to gluten-containing products. Lately, consumers interest in the role of nutrition for health and wellbeing seems a priority. Therefore, today, the main concern of the industry is to innovate, meet and satisfy consumer requirements. In the baking industry that trend has prompted the development of baked goods keeping in mind the healthy concept. Enrichment of formulations, physical treatment of raw materials and the usage of noncommon flour sources are alternatives for enhancing the health benefits of gluten-free baked foods. In that scenario, some other approaches like the exploration of the use of

24 4 Analytical research reports 23 enzymes as healthy aids or the use of smart starch as vehicle of functional ingredients must be encouraged [16-17]. Acknowledgements The financial support of the Spanish Ministry of Economy and Competitiveness (Project AGL C2-1-R) and the European Regional Development Fund (FEDER) is acknowledged. References 1. Arranz E, Fernandez-Bañares F, Rosell CM, Rodrigo L, Peña AS (eds): Advances in the understanding of gluten related pathology and the evolution of gluten-free foods. OmniaScience, Barcelona, Spain, 2015; Open access. omniascience.com/monographs/index.php/monograficos/issue/view/24 2. Rosell CM, Barro F, Sousa C, et al. Cereals for developing gluten-free products and analytical tools for gluten detection. J Cereal Sci 2014; 59: Houben A, Höchstötter A, Becker T. Possibilities to increase the quality in glutenfree bread production: an overview. Eur Food Res Technol 2012; 235: Zannini E, Jones JM, Renzetti S, Arendt EK. Functional replacements for gluten. Annu Rev Food Sci Technol 2012; 3: Renzetti S, Rosell CM. Role of enzymes in improving the functionality of proteins in non-wheat dough systems. J Cereal Sci 2016; 67: Matos ME, Rosell CM. Quality indicators of rice based gluten free bread like products: relationships between dough rheology and quality characteristics. Food Bioprocess Technol 2013; 6: Matos ME, Rosell CM. Relationship between instrumental parameters and sensory characteristics in gluten-free breads. Eur Food Res Technol 2012; 235: Matos ME, Rosell CM. A review: understanding gluten free dough for reaching breads with physical quality and nutritional balance. J Sci Food Agric 2015; 95: Saturni L, Ferretti G, Bacchetti T. The gluten-free diet: Safety and nutritional quality. Nutrients 2010; 2: Matos ME, Rosell CM. Chemical composition and starch digestibility of different gluten free breads. Plant Food Human Nutr 2011; 66: Krupa-Kozak U, Bączek N, Rosell CM. Application of dairy products as technological and nutritional improvers of calcium-supplemented gluten-free bread. Nutrients 2013; 5: Open access.

25 24 Alternatives for developing gluten-free bakery foods 12. Gularte MA, Gómez M, Rosell CM. Impact of legume flours on quality and in vitro digestibility of starch and protein from gluten-free cakes. Food Bioprocess Technol 2012; 5: de la Hera E, Rosell CM, Gómez M. Effect of water content and flour particle size on gluten-free bread quality and digestibility. Food Chem 2014; 151: Cornejo F, Caceres PJ, Martínez-Villaluenga C, et al. Effects of germination on the nutritive value and bioactive compounds of brown rice breads. Food Chem 2015; 173: Ouazib M, Garzón R, Zaidi F, et al. Germinated, toasted and cooked chickpea as ingredients for breadmaking. J Food Sci Technol 2016; 53: Benavent-Gil Y, Rosell CM. Comparison of porous starches obtained from different enzyme types and levels. Carbohydrate Polymers 2017; 157: Dura A, Yokoyama W, Rosell CM. Glycemic response to corn starch modified with cyclodextrin glycosyltransferase and its relationship to physical properties. Plant Foods Human Nutr 2016; 71:

26 4 Analytical research reports Detection of gluten in products containing barley: A proposal for C-hordein as reference material Xin Huang 1, Päivi Kanerva 2, Hannu Salovaara 1, Tuula Sontag-Strohm 1 1 Department of Food and Environmental Sciences, University of Helsinki, Helsinki, Finland 2 Fazer Mills, Oy Karl Fazer Ab, Lahti, Finland Introduction When measuring residual barley prolamin (hordein) contamination in gluten-free products by the R5 ELISA method, the concentration of prolamin is overestimated with the gliadin standard [1-3]. The reason for this may be that the composition of the gliadin standard is different from the composition of hordeins. A hordein standard is needed for barley prolamin quantification instead of the gliadin standard. C-hordein, the primary structure of which is almost entire repeats of PQQPFPQQ, is strongly recognised by the R5 antibody and has times more reactivity than the reference gliadin [4]. The aim of this study was to investigate the proportion of C-hordein in whole barley hordein, in order to explain the hordein overestimation with a gliadin reference material in R5 antibody-based ELISA. An additional aim was to determine whether a reference material using C-hordein could be used to quantify hordein, for example, to determine the barley contamination in gluten-free ingredients and products. Materials and methods Twenty-nine barley cultivars from Finland for feed and malt purposes were selected for this study (Boreal Plant Breeding Ltd.). The total hordein of these cultivars were extracted by 40% (v/v) aqueous 1-propanol with 5% (v/v) 2-mercaptoethanol, and the hordein composition was determined by reversed-phase-hplc by the peak area on a C8 column. C-hordein, B-hordein and D-hordein were collected from the C8 column and their protein content was determined with a bovine serum albumin standard. Hordein fractions were analysed in a sandwich gliadin kit (R7006, R-Biopharm, Darmstadt, Germany) to evaluate their immunoreactivities against the R5 antibody. Barley flour cultivar Elmeri, Einar and Marthe with different C-hordein proportions (33.1%, 25.6% and 17.4%) were selected for spiking in gluten-free oat flour (Provena, Raisio Nutrition Ltd. Finland) to mimic the barley contamination in oat products. The hordein concentration was determined by HPLC, R5 sandwich ELISA with gliadin standard calibration, and with 40% C-hordein standard. The C-hordein was isolated and purified in a preparative ion-exchange column and lyophilised, and 40% C-

27 26 C-hordein as reference material for barley gluten hordein standard was prepared by mixing the protein solution of same concentration 4 : 6 (C-hordein : bovine serum albumin, which does not react with R5 antibody). Results and discussion The C-hordein content of whole hordein of the 29 cultivars ranged 2-fold, from 16.5% to 33.1%. There was slight variation in C-hordein content of the same cultivar Elmeri from 2010, 2014 and 2015 (33.1%, 29.2% and 28.1%). Taken the popularity of the barley cultivars into account, the average C-hordein content of whole hordein in Finland was 25-26%. The corresponding protein group to the C-hordeins in wheat are the ω1,2-gliadins, which shows about 70% sequence homology, with a similar repetitive sequence in the central domain of PFPQQPQQ. The ω-gliadin content of total gliadin has been reported to range from 6% to 20% [5], and from 10% to 19% [6], which is in general lower than the content of C-hordein. The gliadin standard contains 11.3% -gliadin of total gliadin by HPLC analysis [7]. Figure 1. Reaction of isolated hordeins against R5 antibody in sandwich ELISA. Three types of C-hordein and B-hordein were from cultivars Harbinger, Barke and NFC Tipple. D-hordein was from cv. Harbinger The reactivity of D-, C- and B-hordeins against the R5 antibody varied widely in sandwich ELISA (Fig. 1). C-hordein was times more reactive than the gliadin standard, which in turn was 8-25 times more reactive than B-hordein. The slope of the curve indicated that C-hordein and gliadin standard had similar affinity with the R5 antibody, while B-hordein had less, and D-hordein had almost none. The three types of C-hordein reacted similarly with R5 antibody, although their HPLC patterns were different, as well as three types of B-hordein. The varying reactivity of hordein subunits against the R5 antibody is attributable to the number of epitopes. The main

28 4 Analytical research reports 27 R5 epitope, QQPFP, appeared 13 times in C-hordein (Uniprot Q40055), and minor epitopes QQPYP, QQTFP, PQPFP and QLPFP appeared once each. One main QQPFP epitope and 7 minor epitopes were found in B3 hordein (Uniprot I6TEV5), and 5 QQPFP epitopes in B1 hordein (Uniprot P06470). Only one QQPFP epitope was found in γ3-hordein (Uniprot P80198) and no R5 epitope was found in D-hordein (Uniprot Q84LE9) [8]. In sandwich ELISA, the affinity (the slope) of C-hordein with R5 antibody behaved similarly to the gliadin standard, and at a ratio of 3 C-hordein : 7 bovine serum albumin (30% C-hordein), the reaction almost matched that of the gliadin standard (Fig. 2). The curves of purified whole hordein of common cultivars, such as cv. Barke and NFC tipple (C-hordein proportions 24.5% and 28.1% respectively), were above that of the gliadin standard and between that of the 30% and 50% C-hordein standard. The curve of cv. KWS Asta, with its low C-hordein proportion (16.5%), was close to the gliadin standard curve and that of 30% C-hordein. The whole hordein of a barley cultivar with low C-hordein content acted like wheat gliadin against R5 antibody, however, the barley cultivars usually have higher C-hordein content than that. C- hordein mixed with inert protein in the right ratio presented the whole hordein in R5 analysis. Figure 2. Reaction of purified whole hordein of 6 cultivars in R5 sandwich ELISA compared with 30%, 40% and 50% C-hordein standards and gliadin standard

29 28 C-hordein as reference material for barley gluten When measuring the prolamin concentration of prolamin in barley-contaminated oats, with the 40% C-hordein standard, the estimated prolamin concentration was 1.2 times (cv. Elmeri), 0.85 times (cv. Einar) and 0.63 times (cv. Marthe) the HPLC results, however, the concentration calibrated by gliadin standard was 2.5 times (cv. Elmeri), 1.8 times (cv. Einar), and 1.2 times (cv. Marthe) the HPLC results (Fig. 3). For cv. Elmeri and Einar, the estimated value by the 40% C-hordein standard were not significantly different from those determined by HPLC, but for cv. Marthe the estimate was significantly lower, until the standard was changed to 30% C-hordein. Figure 3. Prolamin concentration of gluten-free oat flour spiked with three barley flours, determined by HPLC, R5 sandwich ELISA with 40% C-hordein standard, and R5 sandwich ELISA with gliadin standard. Error bars show standard error Conclusion This study determined that the high proportion of C-hordein in total hordein is the reason for the consistent overestimation of hordein by the R5 ELISA assay which uses gliadin as reference material in gluten-free analysis. We isolated C-hordein and propose it as the reference material for quantifying hordein concentration in glutenfree food originated from barley, including those that may have been contaminated with barley.

30 4 Analytical research reports 29 References 1. Kanerva PM, Sontag-Strohm TS, Ryöppy PH, et al. Analysis of barley contamination in oats using R5 and ω-gliadin antibodies. J Cereal Sci 2006; 44: Hernando A, Mujico JR, Mena MC, et al. Measurement of wheat gluten and barley hordeins in contaminated oats from Europe, the United States and Canada by Sandwich R5 ELISA. Eur J Gastroenterol Hepatol 2008; 20; Mujico JR, Mena MC, Lombardía M, et al. On the way to reliable quantification of barley hordeins using the R5 ELISA technique. In: Stern M (eds): Proceedings of the 22nd meeting working group on prolamin analysis and toxicity. Verlag Wissenschaftliche Scripten, Zwickau, Germany, 2008; pp Huang X, Kanerva PM, Salovaara HO, et al. Degradation of C-hordein by metalcatalysed oxidation. Food Chem 2016; 196: Wieser H, Seilmeier W, Belitz HD. Quantitative determination of gliadin subgroups from different wheat cultivars. J Cereal Sci 1994; 19: Daniel C, Triboi E. Effects of temperature and nitrogen nutrition on the grain composition of winter wheat: effects on gliadin content and composition. J Cereal Sci 2000; 32: Van Eckert R, Berghofer E, Ciclitira PJ, et al. Towards a new gliadin reference material-isolation and characterisation. J Cereal 2006; 43: Tanner GJ, Blundell MJ, Colgrave, ML, et al. Quantification of hordeins by ELISA: The correct standard makes a magnitude of difference. PLoS One 2013; 8(2): e56456.

31 30 C-hordein as reference material for barley gluten

32 4 Analytical research reports Quantitation of the 33-mer peptide from α-gliadins in wheat flours by LC-MS/MS Kathrin Schalk, Christina Lang, Herbert Wieser, Peter Koehler, Katharina A. Scherf Deutsche Forschungsanstalt für Lebensmittelchemie, Leibniz Institut, Freising, Germany Introduction The dietary intake of storage proteins (gluten) from wheat (gliadins, glutenins), rye (secalins), and barley (hordeins) is known to cause coeliac disease (CD) in genetically predisposed individuals. A strict lifelong gluten-free diet is currently the only available therapy. All gluten proteins contain CD-active epitopes [1], which are resistant to cleavage by human gastric, pancreatic, and brushborder enzymes. A 33-mer peptide from α2-gliadin (LQLQPFPQPQLPYPQPQLPYPQPQLPYPQPQPF) was shown to survive gastrointestinal digestion and has frequently been described as most immunodominant gluten peptide [2,3], because it comprises three overlapping DQ2.5/T-cell epitopes, PFPQPQLPY (DQ2.5-glia-α1a, one copy), PYPQPQLPY (DQ2.5-glia-α1b, two copies), and PQPQLPYPQ (DQ2.5-glia-α2, three copies) [1]. Due to its unique structure, the 33-mer peptide plays an important role in the scientific literature with 570 results for a search in the database ScienceDirect with 33 mer and coeliac disease as keywords (as of October 29, 2016). The 33-mer was also used as an antigen to produce two monoclonal antibodies (A1 and G12), which are now used in enzyme-linked immunosorbent assays to determine gluten contents in foods labelled as gluten-free [4]. DNA-sequencing of eleven α-gliadins (α1 - α11) from the Norwegian common (bread) wheat (Triticum aestivum) cultivar (cv.) Mjølner (MJO) revealed that only α2-gliadin contained the 33-mer amino acid sequence at positions [5]. According to a BLAST search in the UniProtKB database within 587 entries for α-gliadins from Triticum sp., the 33-mer sequence (100% identity) was found in only 17 protein sequences from T. aestivum and in three from T. spelta (as of September 13, 2016). Of these 20 sequences, only three have evidence at transcript level (Q9M4L6, Q1WA39 and A5JSA6) inferred from three Chinese wheat cultivars, but only one (P18573) has evidence at protein level based on data of the Norwegian wheat cv. MJO. Despite the high number of papers featuring the 33-mer, there is no information on the presence and quantities of the 33-mer peptide in different wheat species and cultivars. Therefore, the aim of the present study was to develop a stable isotope dilution assay (SIDA) combined with liquid chromatography tandem mass spectrometry (LC- MS/MS) for the determination of the presence and quantity of the 33-mer. Fifty-seven flours of different wheat species from around the world were investigated, including hexaploid common wheat (T. aestivum) and spelt (T. aestivum ssp. spelta), tetraploid

33 32 Quantitation of the 33-mer peptide by LC-MS/MS durum wheat (T. turgidum durum) and emmer (T. turgidum dicoccum), and diploid einkorn (T. monococcum) to assess the importance of this CD-active peptide. Materials and methods Preparation and characterization of flour samples Twenty-three modern and 15 old (year of first registration before 1950) common wheat cultivars from different harvest years grown worldwide, and one rye cultivar (cv. Visello, harvested in 2013) were either obtained as flours or milled on a Quadrumat Junior mill (Brabender, Duisburg, Germany) and sieved (mesh size 0.2 mm). Two spelt, durum wheat, emmer, and einkorn cultivars each were milled on a Laboratory 3100 cross beater mill (Perten Instruments, Hamburg, Germany) to wholemeal flours. The crude protein content (nitrogen content x 5.7) of the flours was determined by the Dumas combustion method. The contents of albumins/globulins, α-gliadins, gliadins, glutenins, and gluten (sum of gliadins and glutenins) were determined by modified Osborne fractionation of the flours followed by RP-HPLC-UV (210 nm) analysis [6]. Sample preparation The flours ( mg) were defatted with pentane/ethanol (95/5, v/v; 2 x 2.0 ml). After removal of the albumins/globulins, the gliadins were extracted with 60% (v/v) ethanol, dried, and re-suspended in a TRIS-HCl-buffer (ph 7.8). The stable isotope labelled standard (*33-mer, LQLQP*FPQPQLPYPQPQLPYPQPQLPYPQ*PQ*P*F, with *F: L-[ 13 C 9 ][ 15 N]-phenylalanine and *P: L-[ 13 C 5 ][ 15 N]-proline) was added (3 µg) and the gliadin-peptide mixture hydrolysed with α-chymotrypsin (enzyme-to-protein ratio of 1:200) for 24 h at 37 C. Trifluoroacetic acid (5 µl) was added to stop the digestion. The peptide mixture was dried, re-dissolved in formic acid (FA) (0.1%, v/v, 500 µl), filtered (0.45 µm) and analysed by LC-MS/MS. LC-MS/MS A triple-stage quadrupole mass spectrometer (TSQ Vantage, Thermo Fisher Scientific, Dreieich, Germany) was used in the ESI positive mode. The mass spectrometer was operated in the multiple reaction monitoring (MRM) mode using the most abundant MRM transition as quantifier and the three MRM transitions following in abundance as qualifiers (Tab. 1). A declustering voltage of -10 V was set for all transitions. The 33-mer and the labelled *33-mer peptides were dissolved in FA (0.1%, v/v, 10 µg/ml). These two stock solutions were mixed in molar ratios n (*33-mer)/n (33- mer) between 9.2 and 0.02 (1+9, 1+4, 1+3, 1+1, 3+1, 4+1, 9+1, 14+1, 19+1, 29+1, and 39+1) for calibration. An UltiMate 3000 HPLC system (Dionex, Idstein, Germany) was coupled to the mass spectrometer equipped with an XBridge Peptide 3.5 μm BEH- C 18 column (1.0 x 150 mm, 13 nm; Waters, Eschborn, Germany). The LC conditions were set as follows: solvent A, FA (0.1%, v/v) in water, solvent B, FA (0.1%, v/v) in

34 4 Analytical research reports 33 acetonitrile; gradient 0-5 min 5% B, 5-22 min 5-55% B, min 90% B; min 90-5% B, min 5% B, flow rate, 0.1 ml/min; injection volume, 10 µl, column temperature, 22 C. Table 1. Multiple reaction monitoring (MRM) parameters of the 33-mer peptide and the stable isotope labelled *33-mer peptide. Peptide Precursor ions m/z (charge state) Product ions 1 m/z 33-mer (4+) (y2) (3+) (y4) (y6 ) (y8) 3 *33-mer (4+) (y2) (3+) (y4) (y6) (y8) 3 Collision energy (V) Retention time (min) Charge state: 1+, 2 Precursor to product ion transitions were used as quantifier, 3 Precursor to product ion transitions were used as qualifiers The limits of detection (LOD) and quantitation (LOQ) of the LC-MS/MS method for the 33-mer peptide were determined. Rye flour was used as blank, because of the absence of α-gliadins. The rye prolamin extract was spiked at 7 different concentrations ( mg/kg) of 33-mer peptide and the samples were prepared and analysed as described above. The LOD was calculated based on a signal-to-noise ratio (S/N) of 3, and the LOQ on an S/N ratio of 10. Statistics Linear Pearson s product moment correlations were calculated between contents of 33- mer and α-gliadins, gliadins, gluten or crude protein for all analysed wheat and spelt cultivars. Principal component analysis (PCA) was carried out with XLStat 2016 (Addinsoft, New York, NY, USA) to determine if the contents of 33-mer, α-gliadins, gliadins, gluten, and crude protein could be used to differentiate between spelt, modern and old common wheat cultivars Results and discussion A [ 13 C 28 ]- and [ 15 N 4 ]-labelled *33-mer peptide (LQLQP*FPQPQLPYPQPQLPYPQ PQLPYPQ*PQ*P*F, with *F: L-[ 13 C 9 ][ 15 N]-phenylalanine and *P: L-[ 13 C 5 ][ 15 N]- proline, monoisotopic mass ) was used as stable isotope labelled internal standard. It differed in 32 mass units compared to the unlabelled analyte (33-mer, monoisotopic mass ). Based on the fragmentation pattern of the 33-mer, the [ 13 C]/[ 15 N]-labelled amino acids were positioned in such a way that the label remained in the product ions (Tab. 1). The response factor was determined using the peak area ratio A (*33-mer)/A (33-mer) at different values of n (*33-mer)/n (33-mer) between

35 34 Quantitation of the 33-mer peptide by LC-MS/MS 0.02 and 9.2 within the linear range based on the MRM transitions m/z (*33-mer) and m/z (33-mer). As expected from SIDA, the response factor was The LOD of the LC-MS/MS method to detect the 33-mer peptide was 13.1 µg/g rye flour and the LOQ was 47.0 µg/g rye flour. The 33-mer was determined in flours of 23 modern and 15 old common wheats from different harvest years and two spelt cultivars. In this context, old common wheat is defined as a cultivar from T. aestivum with its year of first registration prior to All flours were characterised including determination of crude protein contents and quantitation of α-gliadins, gliadins, glutenins, and gluten after modified Osborne fractionation combined with RP-HPLC [6,7]. The 33-mer was present in all common wheat and spelt flours in a range from 90.9 to µg/g of flour (Fig. 1A). Overall, the modern wheat cv. Yumai-34 (harvested in 2014, Y14) had the highest (602.6 µg/g flour) and the old wheat cv. Ackermanns Brauner Dickkopf (ABD) the lowest (90.9 µg/g flour) amount of 33-mer. Most of the modern and old wheat flours contained the 33-mer in a range of µg/g flour with an overall average of 368 ± 109 µg/g flour. Special attention was directed to cv. MJO, because the 33-mer was first identified in this cultivar [5], which had a 33-mer content of µg/g flour. A certain trend, e.g., that modern wheat cultivars generally contain higher amounts of 33-mer than old wheat or spelt cultivars could not be derived from the data. The 33-mer contents of all analysed flours were also calculated based on the amount of α-gliadins (Fig. 1B). MJO had the highest content of 33-mer in α-gliadins (23.2 mg/g α-gliadins) caused by the high 33-mer content and the low amount of α-gliadins (2.2%) in flour. ABD had the lowest amount of 33-mer in α-gliadins (4.1 mg/g α- gliadins). The overall average content was 11.7 ± 3.1 mg/g α-gliadins. Because there is virtually no data in the literature, it was difficult to compare these values with earlier studies, but one paper by van den Broeck et al. on the quantitation of the 33-mer using LC-MS with external calibration found comparable values for two wheat cultivars [8]. Correlations and PCA The 33-mer contents of the 51 modern and old common wheat and spelt cultivars (based on flour) were correlated to the contents of α-gliadins, gliadins, gluten, and crude protein. A weak correlation (r = 0.568) was observed between 33-mer and α- gliadin contents, but there was no correlation to gliadin contents (r = 0.469), gluten contents (r = 0.526) or crude protein contents (r = 0.466). PCA with 33-mer, α-gliadins, gliadins, gluten, and crude protein contents of the 51 flours was performed to assess whether these variables could be used to differentiate between spelt, modern common wheat, and old common wheat cultivars (Fig. 2). However, PCA revealed that these five variables were unsuitable to differentiate between spelt, modern common wheat, and old common wheat cultivars. Five old common wheat cultivars were placed on the far left, but the other ten old cultivars

36 4 Analytical research reports 35 were located right in the middle at similar coordinates as the modern common wheat cultivars. The two spelt cultivars were also situated in between the common wheat cultivars. Figure 1. Contents of 33-mer based on flour [µg/g] (A) and based on α-gliadins [mg/g] (B). 23 modern and 15 old common wheat cultivars (49 samples in total due to multiple harvest years) and two spelt cultivars were analysed. Wheat cultivars registered prior to 1950 were designated as old

37 36 Quantitation of the 33-mer peptide by LC-MS/MS 3 x/y 3.0/8.7 2 MJO 33 mer Component 2 (13.3 %) α gliadin gluten Y14 ABD 2 3 Old wheat cultivars Modern wheat cultivars Spelt cultivars crude protein gliadin Component 1 (81.6 %) Figure 2. Principal component analysis biplot of data for 33-mer, α-gliadin, gliadin, gluten, and crude protein contents. 23 modern and 15 old common wheat (49 samples in total due to multiple harvest years) and two spelt cultivars were analysed. Wheat cultivars registered prior to 1950 were designated as old. ABD, wheat cv. Ackermanns Brauner Dickkopf, MJO, wheat cv. Mjølner, Y14, wheat cv. Yumai-34, harvest year 2014) The 33-mer peptide was also analysed in two durum wheat and two emmer cultivars (genome AABB) as well as in two diploid einkorn cultivars (genome AA), but it was not detected in each of these wheat species (< LOD). In comparison to hexaploid common wheat, durum wheat, emmer, and einkorn do not contain the D-genome, which originated from hybridisation of T. turgidum dicoccum (genome AABB) with Aegilops tauschii (genome DD). The absence of the 33-mer peptide can be explained by the fact that this peptide is encoded by genes located in the Gli-2 locus on chromosome 6D, which is missing in durum wheat, emmer, and einkorn [5].

38 4 Analytical research reports 37 Conclusion This is the first study to establish a SIDA combined with LC-MS/MS to quantitate the immunodominant 33-mer peptide from α2-gliadin in wheat flours. All 40 modern and old common wheat and spelt cultivars analysed contained the 33-mer peptide (51 flour samples in total, because several flours were available from different harvest years). The special attention paid to this peptide in the scientific literature seems to be legitimated not only because of its unique structure containing six copies of three overlapping coeliac-active epitopes, but also because of its presence in all hexaploid wheat cultivars analysed in this study. Further work will focus on correlating the 33- mer content analysed by LC-MS/MS with the gluten content determined by ELISA using the G12 antibody, which was raised against the 33-mer. Acknowledgement The authors would like to thank Andreas Börner (Leibniz Institute of Plant Genetics and Crop Plant Research, Resources Genetics and Reproduction, Gatersleben, Germany), Friedrich Longin (University of Hohenheim, LSA - Resarch Group Wheat, Stuttgart, Germany), Anette Moldestad (Nofima, Ås, Norway), Roland Poms (Imprint Analytics, Neutal, Austria), Sándor Tömösközi (Budapest University of Technology and Economics, Department of Applied Biotechnology and Food Science, Budapest, Hungary), and Bin Xiao Fu (Canadian Grain Commission, Grain Research Laboratory, Winnipeg, Canada) for providing wheat grains and flours. References 1. Sollid LM, Qiao S-W, Anderson RP, et al. Nomenclature and listing of celiac disease relevant gluten T-cell epitopes restricted by HLA-DQ molecules. Immunogenetic 2012; 64: Shan L, Molberg Ø, Parrot I, et al. Structural basis for gluten intolerance in celiac sprue. Science 2002; 297: Shan L, Qiao S-W, Arentz-Hansen H, et al. Identification and analysis of multivalent proteolytically resistant peptides from gluten: implications for celiac sprue. J Proteome Res 2005; 4: Morón B, Cebolla A, Manyani H, et al. Sensitive detection of cereal fractions that are toxic to celiac disease patients by using monoclonal antibodies to a main immunogenic wheat peptide. Am J Clin Nutr 2008; 87: Arentz-Hansen H, McAdam SN, Molberg Ø, et al. Production of a panel of recombinant gliadins for the characterisation of T cell reactivity in coeliac disease. Gut 2000; 46:

39 38 Quantitation of the 33-mer peptide by LC-MS/MS 6. Wieser H, Antes S, Seilmeier W. Quantitative determination of gluten protein types in wheat flour by reversed-phase high-performance liquid chromatography. Cereal Chem 1998; 75: Schalk K, Lang C, Wieser H, et al. Quantitation of the immunodominant 33-mer peptide from α-gliadin in wheat flours by liquid chromatography tandem mass spectrometry. Sci Rep 2017; doi: /Srep van den Broeck HC, Cordewener JHG, Nessen M, et al. Label free targeted detection and quantification of celiac disease immunogenic epitopes by mass spectrometry. J Chrom A 2015; 1391:

40 4 Analytical research reports The gluten content of wheat starches Tanja Šuligoj, H. Julia Ellis, Paul J. Ciclitira Department of Gastroenterology, Kings College, St Thomas Hospital, London, United Kingdom Introduction The only generally accepted treatment for coeliac disease (CD) is a lifelong strict gluten-free diet that involves avoidance of wheat, rye and barley. Wheat gluten contains gliadin, low (LMWG) and high (HMWG) molecular weight glutenin proteins, all three of which have been shown to be CD-toxic [1-3]. Many gluten-free foods are available. This includes those that are commercially marketed, 80% of which in the UK are based on purified wheat starch. Foods that are supplied as gluten-free are required to contain <20 mg/kg gluten and those that are labelled "very low gluten" mg/kg gluten. The only FAO certified assay to quantify the gluten content of foods for individuals with CD is based on the R5 monoclonal antibody (mab) that recognises gliadin but not glutenin [4]. The value for the gluten content of a given food for this assay is determined by quantifying the gliadin content and multiplying the value by two to yield the gluten content of a given food. This extrapolation, based on the gliadin content may be invalid due to the differing solubility of gluten proteins, that is gliadin and glutenins, when food is processed. Aims We wished to improve the extent and accuracy of quantification of CD-triggering peptides in purified wheat starch that is a common ingredient of many commercially available processed gluten-free foods for individuals with CD. Materials and methods We have generated three mabs to wheat gluten proteins. This includes PN3 to wheat gliadin that was raised against and detects coeliac-toxic A-gliadin AA31-49 [5,6], CDC5 to the CD-toxic immunodominant epitope in wheat gliadin that was raised against and detects α2-gliadin AA57-75 [7] and CDC7 to wheat glutenin generated to the protein 1Dy10 HMWG glutenin subunits (HMWG) [8]. We developed three separate competitive ELISAs employing the three separate mabs, PN3, CDC5 and CDC7. We assessed the gluten content of three wheat starches termed A, B & C that are supplied as standards for the Transia kit that is marketed to quantify the gluten content of foods based on the use of a mab raised against ω-gliadin [9].

41 40 The gluten content of wheat starches Results and discussion Gliadin contents of wheat starches A, B and C were 34.2, 52.9 and mg/kg as determined by PN3 mab. Gliadin contents of the wheat starches measured using CDC5 mabs followed the same trend of increasing gliadin content from starch A to C, but the values were higher. Gliadin contents were 106.9, and mg/kg. Starches A, B and C contained 114.1, and mg/kg glutenin as assessed with CDC7 mabs (Tab. 1). Table 1. Gliadin and glutenin content (in mg/kg) of wheat starches A, B and C as determined with PN3, CDC5 and CDC7 mab. Antigen measurement Starch A Starch B Starch C Gliadin (mg/kg) with PN Gliadin (mg/kg) with CDC Glutenin (mg/kg) with CDC Gluten contents were then calculated based on measurements of the three mabs. Two approaches were undertaken: a) by following the standard method of extrapolating gliadin content to total gluten by multiplying the gliadin content by factor 2 ; b) by summing up gliadin and glutenin content to obtain the gluten content. Two different results were obtained, depending on whether gliadin content was measured with PN3 or CDC5 mab (Tab. 2). When PN3 mab measurement was used to extrapolate the gliadin content of starch A to total gluten, the obtained value was 68.4 mg/kg gluten which is within the limit for very low gluten labelling of foodstuffs. When another anti-gliadin mab (CDC5) was used for the same starch, the gluten content was more than 3 times higher (213.8 mg/kg), exceeding the 100 mg/kg cut-off value for very low gluten. Summing up the values of gliadin and glutenin measurements to obtain total gluten led to two different results: and 221 mg/kg depending on whether values of PN3 or CDC5 measurements were taken to be summed up with CDC7 measurements (Tab. 2). Interestingly, the calculation for total gluten based on the approach gluten = 2 x gliadin (PN3) was more than 2-fold lower than when gluten was calculated by summing up gliadin (PN3) plus glutenin (CDC7) which equalled mg/kg for wheat starch A. On the contrary, for CDC5 mab these two approaches resulted in very similar final gluten contents (213.8 and 221 mg/kg respectively) (Tab. 2). Similarly, when the gliadin content of wheat starch B was extrapolated to total gluten (by multiplying the gliadin content by 2), the obtained value was mg/kg for PN3 measurement and 7-fold higher gluten content (741.6 mg/kg) was seen for CDC5 measurement. When total gluten of starch B was obtained by the other approach, i.e. summing up the values of gliadin and glutenin (CDC7) measurements, they resulted in 484 and mg/kg gluten for PN3 and CDC5 measurements, respectively. Gluten content calculated by gluten = 2 x gliadin as opposed to gluten = gliadin + glutenin

42 4 Analytical research reports 41 (CDC7) differed 4.6-fold for PN3 mab measurements and 1.1-fold for CDC5, the higher values obtained by the gluten = gliadin + glutenin approach (Tab. 2). The results for wheat starch C had a similar trend. Gluten content obtained by multiplying gliadin measurements by factor 2 resulted in 4.4-fold higher total gluten content for CDC5 measurement ( mg/kg) than PN3 measurement (469.2 mg/kg). The other approach whereby glutenin content (obtained with CDC7 measurement) was summed up with gliadin content resulted in 3.6-fold increase of gluten content for PN3 mab measurements (from to 1716 mg/kg) and 1.2-fold increase of gluten content for CDC5 mab measurements (from to mg/kg) (Tab. 2). Table 2. Gluten content (in mg/kg) of wheat starches A, B and C as determined by multiplying gliadin content by 2 versus summing up the measurements of gliadin and glutenin content. Gluten content (in mg/kg) Starch A Starch B Starch C a) gluten = 2 x gliadin (PN3) a) gluten = 2 x gliadin (CDC5) b) gluten = gliadin (PN3) + glutenin (CDC7) b) gluten = gliadin (CDC5) + glutenin (CDC7) Further, ratios of glutenin to gliadin content of the wheat starches were determined by dividing the glutenin values obtained with CDC7 mab by gliadin values assessed either by PN3 or CDC5 mab (Tab. 3). Table 3. Ratios of glutenin to gliadin contents in wheat starches A, B and C depending on which gliadin monoclonal antibody (PN3 or CDC5) is used for comparison with CDC7 mab measurements. Glutenin : gliadin ratio Starch A Starch B Starch C CDC7 : PN CDC7 : CDC Gliadin content of starches A, B and C depended on whether PN3 or CDC5 was chosen for the measurement (Tab. 1). Ratios of gliadin contents in the three wheat starches were determined by dividing the gliadin content obtained with CDC5 by gliadin content obtained by PN3 mab. The scale of difference in gliadin content varied amongst starches (3.1- to 7.0-fold) (Tab. 4). Table 4. Ratios of gliadin contents in wheat starches A, B and C as obtained with the two gliadin antibodies (CDC5 and PN3). Gliadin : gliadin ratio Starch A Starch B Starch C CDC5 : PN

43 42 The gluten content of wheat starches Discussion We demonstrated that a broadened repertoire of mabs specific for CD-triggering peptides enabled improved measurement of gluten in foods, by allowing a more realistic measurement of the CD-triggering epitopes within the glutenins. This applied particularly to the measurements where PN3 mab was used for measuring gliadin content and then obtaining total gluten either by the standard method or by summing up gliadin and glutenin measurements. This observation was less applicable to CDC5 measurements as multiplying gliadin content obtained by CDC5 mab by a factor 2 differed very little to obtaining gluten content by summing up its gliadin content with glutenin. The total gluten based on CDC5 and CDC7 mab measurements indicate that the epitopes that these two mabs detect were more equally distributed as opposed to those detected by PN3 and CDC7 mabs in the three starches. None of the three wheat starches were gluten-free, as they all contained more than 20 mg/kg gluten. When anti-gliadin mab PN3 was used for the measurements of gluten contamination of starch A it resulted in values that would classify it as very low gluten foodstuff as it contained less than 100 mg/kg gluten. This was applicable for the standard method of determining the total gluten by multiplying the gliadin value by factor 2. However, when total gluten content was assessed by summing up the values obtained with PN3 mab and anti-glutenin mab CDC7, the gluten values were well above the cut-off value for very low gluten. This data clearly demonstrates the importance of measuring both groups of proteins in gluten responsible for CD toxicity (gliadins and glutenins). This is particularly important for processed foodstuffs like wheat starches where gliadin : glutenin ratios have been shown to vary greatly [10,11]. Glutenin to gliadin ratios of the wheat starches varied between Our results demonstrate that multiplying gliadin content by factor 2 to estimate for the glutenin may be invalid for processed foodstuffs, which is in agreement of Wieser and Koehler s [10] observations. Measurement of gliadin alone therefore cannot predict total gluten content in foods. The standard method of multiplying gliadin content by 2 would lead to gross underestimation of gluten content in our wheat starches if the antibody used for detection of gliadins was PN3 mab. The lower glutenin to gliadin ratios were obtained when comparing the glutenin contents with gliadin determined with CDC5 mabs. The higher ratio of glutenin to gliadin obtained with PN3 as anti-gliadin antibody can be explained by the lower amounts of the gliadin peptide that PN3 detected in the wheat starches. This was further confirmed by calculating the gliadin to gliadin ratios determined by PN3 and CDC5 antibodies which showed that the amount of detected gliadin in a foodstuff depends greatly on which antibody is used for quantification. This concept was demonstrated previously in a study of van Eckert et al. [12] who showed that two different anti-gliadin antibodies (PN3 and R5) reacted with different individual proteins in different protein sub-fractions of the reference gliadin separated by two dimensional electrophoresis.

44 4 Analytical research reports 43 Further, our results differed from the reference values for gluten contamination of the three wheat starches A, B and C. The reference values were provided in the manufacturer s information sheet and had been obtained using a monoclonal antibody which detects ω-gliadins and were as follows: <100 mg/kg gluten for starch A, mg/kg gluten for starch B and mg/kg for starch C [9]. The value of <100 mg/kg complied with the previous regulations for labelling foods to be glutenfree but not with the current regulations of <20 mg/kg. Our results of gluten contamination did follow the same trend of increasing gluten contamination from starch A to C, but the values were not the same. Gluten contamination assessment with antibodies of different specificity can therefore result in different gluten amounts, which is consistent with Allred and Ritter s observations [13]. Of note, the manufacturer of the three starches A, B and C did not provide information as to which wheat cultivars the starches were obtained from. In this respect we do not know whether the flour from the same cultivar was used and resultant starches subjected further to three different washing processes or whether three different cultivars were used. There is a dilemma in the field of gluten measurement of what should be quantified in order to assess the overall toxicity of foods for CD sufferers [14]. There are several CD-triggering epitopes [15]. It is probably unrealistic to detect all of them. The gliadin fraction of wheat gluten has long been established as CD-triggering. However, the glutenins have only recently been shown to exacerbate the disease. Our monoclonal antibodies detect CD-triggering epitopes distributed amongst both groups of proteins, for which there is substantial clinical data confirming their role in CD pathogenesis. It is interesting, although not surprising, that contamination of wheat starches with glutenins was notably higher than with gliadins. This is likely due to different solubility characteristics of the gluten protein fractions as a result of food processing [13,16,17]. The glutenins are less water-soluble and therefore more likely to stay adsorbed to starch granules after washing [16]. It is therefore crucial to detect glutenin contamination of processed foodstuffs and thereby improve the extent of measured gluten components. Our findings are consistent with Allred [13] who demonstrated that all processed foodstuffs (n = 40) tested in their study contained 4- to 10-fold higher gluten values when assessed with the mab that has high affinity to glutenins as opposed to R5 mab with high affinity for gliadins. Conclusion We suggest that a broadened repertoire of mabs specific for CD-triggering peptides enables improved measurement of gluten in foods for individuals with CD, by allowing a more realistic measurement of the CD-triggering epitopes within the glutenins. The total gluten content depended on the specificity of the mab(s) used for quantitation. In addition, the glutenin to gliadin ratios varied greatly between wheat starches. We therefore suggest that multiplying the gliadin content by a factor of 2 to

45 44 The gluten content of wheat starches estimate the total gluten content of a given nominally gluten-free food, particularly those that are based on purified wheat starch may be invalid for processed foodstuffs. Acknowledgement The authors wish to thank the Rosetrees Trust and Clinical Research Trust for support. References 1. Ciclitira PJ, Evans DJ, Fagg NL, et al. Clinical testing of gliadin fraction in coeliac patients. Clin Sci 1984; 66: Vader W, Kooy Y, van Veelen P, et al. The gluten response in children with coeliac disease is directed towards multiple gliadin and glutenin peptides. Gastroenterol 2002; 122: Dewar DH, Amato M, Ellis HJ, et al. The toxicity of high molecular weight glutenin subunits of wheat to patients with coeliac disease. Eur J Gastroenterol 2006; 18: Osman AA, Uhlig HH, Valdes I, et al. A monoclonal antibody that recognises a potential coeliac-toxic repetitive pentapeptide epitope in gliadin. Eur J Gastroenterol Hepatol 2001; 13: Freedman AR, Galfre G, Gal E, et al. Monoclonal antibody ELISA to quantitate wheat gliadin contamination of gluten-free foods. J Immunol Methods 1987; 98: Ellis HJ, Rosen-Bronson S, O Reilly R, et al. Measurement of gluten using a monoclonal antibody to a coeliac toxic peptide of A-gliadin. Gut 1998; 43: Ellis HJ, Bermudo Redondo M, Šuligoj T, et al. Gluten quantification of foods via the immunodominant gliadin epitope. F Nutr Rep 2016; 1(3): Ellis HJ, Bermudo Redondo C, Šuligoj T, et al. Monoclonal Antibodies to high molecular weight glutenin subunits for use in measurement of gluten in foods. F Nutr Rep 2015; 1(2): Skerritt JH, Hill AS. Monoclonal antibody sandwich enzyme immunoassays for determination of gluten in foods. J Agric Food Chem 1990; 38: Wieser H, Koehler P. Is the calculation of the gluten content by multiplying the prolamin content by a factor of 2 valid? Eur Food Res Technol 2009; 229: Wieser H, Seilmeier W, editor. Determination of gliadin and gluten in wheat starch by means of alcohol extraction and gel permeation chromatography. Proceedings of the 17th Meeting of the Working Group on Prolamin Analysis and Toxicity; 2002; London, UK. Zwickau: Verlag Wissenschaftliche Scripten 2003.

46 4 Analytical research reports van Eckert R, Bond J, Rawson P, et al. Reactivity of gluten detecting monoclonal antibodies to a gliadin reference material. J Cereal Sci 2010; 51: Allred LK, Ritter BW. Recognition of gliadin and glutenin fractions in four commercial gluten assays. J AOAC Int 2010; 93: Ciclitira PJ, Ellis HJ, Lundin KEA. Gluten-free diet - what is toxic? Best Pract Res Clin Gastroenterol 2005; 19: Sollid LM, Qiao SW, Anderson RP, et al. Nomenclature and listing of celiac disease relevant gluten T-cell epitopes restricted by HLA-DQ molecules. Immunogenetics 2012; 64: Kasarda DD, Dupont FM, Vensel WH, et al. surface-associated proteins of wheat starch granules: suitability of wheat starch for celiac patients. J Agric Food Chem 2008; 56: Wieser H, Antes S, Seilmeier W. Quantitative determination of gluten protein types in wheat flour by reversed-phase high-performance liquid chromatography. Cereal Chem 1998; 75:

47 46 The gluten content of wheat starches

48 4 Analytical research reports Comparison of immunomethods for the characterisation of gluten immunogenic peptides in a commercial beer Alba Muñoz-Suano 1, Miguel Ángel Síglez 1, Isabel Comino 2, Lourdes Moreno 2, Ana Real 2, Carolina Sousa 2, María Isabel Torres 3, Elena Quesada-Hernández 1, Ángel Cebolla 1 1 Biomedal SL, Sevilla, Spain 2 Dpto. de Microbiología y Parasitología, Facultad de Farmacia, Universidad de Sevilla, Sevilla, Spain 3 Dpto. de Biología Experimental, Campus Universitario Las Lagunillas, Jaén, Spain Introduction Gluten is present in the most commonly consumed cereals (wheat, barley, rye and oats) and serves as ingredient in many processed foods. Manufacturing of processed foodstuffs digests gluten to different degrees, especially by hydrolysis and fermentation. This digestion of total gluten gives rise to peptides and, ultimately, to amino acids. In the small intestine, some of these peptides are resistant to gastrointestinal digestion and trigger the immune response that causes the symptoms of the disease. This pool of peptides is termed gluten immunogenic peptides (GIP). However, the characterization of these peptides is still incomplete. The great heterogeneity of gluten proteins makes this task complicated and tedious. In the last years, it has been shown that a few highly immunogenic peptides could account for more than 90% of the coeliac-specific response [1-3]. The dominant immunogenic peptide in wheat is the α-gliadin 33-mer [2]. Beer is the most widely consumed alcoholic beverage, both among coeliac and noncoeliac individuals. Its production involves the fermentation of starches, mostly from cereal grains (barley, wheat, maize, rice ). This fermentation hydrolyses gluten proteins contained in the cereal grains and produces GIP which remain in the final product. The differential hydrolysis of prolamins in brewing processes may generate peptide pools with uncertain immunogenicity. Current methods based on the R5 antibody to officially analyse gluten content in beer and grant the gluten-free label may overlook these immunogenic peptides. However, the new generation of monoclonal antibodies (mabs) like A1 and G12 with a sensitivity and specificity for the 33-mer several orders of magnitude higher compared to R5 antibody may result in differences in immunogenicity estimation for hydrolytic prolamins [7]. Beers, due to their diversity, are some of the samples in which the immunomethods may show the highest differences in gluten content measurement. Here, we evaluated the reliability of the methods based on R5 and G12 to estimate the potential toxicity by GIP contained in a commercial beer, which was previously characterised by HPLC-MS and peripheral blood mononuclear cell (PBMC) reactivity from coeliac patients.

49 48 Comparison of immunomethods for the analysis of gluten Materials and methods Beer samples, negative control (rice prolamins), peptide synthesis, and synthetic peptides were used. Patients with active coeliac disease and healthy subjects were included in this study. T-cell isolation from coeliac patients, cell proliferation assays, interferon (IFN)-γ, lateral flow immunoassay (LFIA) A1/G12 (GlutenTox Sticks, Biomedal), competitive ELISA G12 (GlutenTox Competitive G12 Biomedal) and R5 (Ridascreen, R-Biopharm), and immunoprecipitation assays were made as described in [4,5] and are not reproduced here for space reasons. Results and discussion In a previous study, we characterised about 100 Belgian beers by LFIA and ELISA based on G12/A1 mabs (some examples showed in Table 1 and [6]). Although the sandwich ELISA configuration may underestimate the presence of some gluten peptides with only one epitope, LFIA and G12 competitive ELISA provided a similar estimation of gluten content. However, the underestimation appeared to be higher in a R5 sandwich than in the A1/G12 LFIA (Table 1). This observation may indicate that the abundance of tandem epitopes for A1 and G12 is more frequent than that of R5 epitopes. To analyse the differential epitope recognition present in beers, we selected a beer based on the difference in gluten estimation by R5 and G12 ELISA (Table 1, in bold). The Strong Ale 5 was fractionated and characterised with HPLC-MS and the gluten content of each fraction was further analysed using LFIA A1/G12. All immunoreactive fractions contained peptides recognised by A1, G12 and R5. Five peptides were selected according to the presence of epitopes with potential immunogenicity (i.e. reactive to R5, A1 and G12). These peptides were synthesised ([4] and Fig. 1). The R5 competitive ELISA showed 5- to 9-fold less reactivity for the barley beer epitopes compared to the G12 competitive ELISA. A1 competitive ELISA showed an intermediate affinity for the immunogenic peptides compared to R5. The biggest differences in reactivity were found in peptide QP 22.2, which contains two tandem epitopes for R5 and one for A1 (QP 22.2 in Fig.1). QP22.2 reactivity for R5 was sixfold larger than to A1 and a hundred-fold larger than for G12. Interestingly, despite its great reactivity to R5, this peptide induced a very weak reactivity to PBMCs from coeliac patients, slightly superior to the negative control (rice prolamins) (Fig. 2 and [4]). In contrast, the most reactive peptide for G12 (PP 24.1) also confirmed the highest immunogenicity by PBMC activation and IFN-γ production. These results were consistent with those obtained by G12/A1 competitive ELISA, but not according to R5. Therefore, there is no correlation between the reactivity for the R5 mab and the immunogenicity of peptides. Moreover, the highest sensitivity of G12 for such GIP could be an indication of the presence of immunogenicity risks in many cases.

50 4 Analytical research reports 49 Table 1. Gluten levels of the 30 Belgian beer samples analysed with mabs G12/A1 and mab R5 ELISA. Beer Cereal Gluten Content (mg/kg) GlutenTox GlutenTox ELISA Competitive sticks Sandwich R5 ELISA G12 Abbey tripel 1 Barley+wheat > Abbey tripel 2 Barley Abbey tripel 3 Barley <3 Abbey dubbel 1 Barley > Abbey dubbel 2 Barley <3 Abbey dubbel 3 Barley Abbey dubbel 4 Barley <3 <3 <3 Abbey dubbel 5 Barley+wheat Abbey dubbel 6 Barley+wheat+oat Strong ale 1 Barley+wheat Strong ale 2 Barley > Strong ale 3 Barley > Strong ale 4 Barley <3 <3 <3 Strong ale 5 Barley <3 * Fruit lambic 1 Barley+wheat > Fruit lambic 2 Barley+wheat >100 1, Fruit lambic 3 Barley+wheat Fruit lambic 4 Barley+wheat > Fruit lambic 5 Barley <3 <3 < 3 Specialty 1 Millet <3 <3 < 3 Specialty 2 Barley+corn <3 <3 < 3 Specialty 3 Barley+corn <3 <3 < 3 Season 1 Barley+wheat > Season 2 Barley > White 1 Barley+wheat > White 2 Barley+wheat > Sour ale 1 Barley > Sour ale 2 Barley <3 <3 <3 Pale lager 2 Barley > Pale lager 1 Barley * The gluten content of Strong Ale 5 was also estimated by Competitive ELISA R5: 9.27 ppm

51 50 Comparison of immunomethods for the analysis of gluten mab G12 mab A1 mab R5 Figure 1. Relative affinity of G12, A1 and R5 mabs for different immunoreactive peptides from the barley beer previously characterised by HPLC-MS and PBMC activation. Figure 2. Potential immunogenicity of PP 24.1 and QP (A). Proliferative responses of PBMCs to different peptides. (B). IFN-γ production by PBMCs with different peptides. Results are expressed as mean ± SD of duplicated cultures (n = 14). Gliadin and oryzein were used as the positive and negative control, respectively, and significant differences with respect to gliadin at **p<0.005 are shown Next, we wanted to assess the similarities between the pool of GIP detectable by G12 and those detectable by R5. To do so, we fractionated the Strong Ale 5 beer with immunochromatography using agarose beads conjugated with G12 mab (Fig. 3). Three fractions were obtained: Input (barley beer), Flow Through (barley beer minus the G12 reactive peptides) and Output (peptides bound to the G12 columns that are released by heat denaturation). All three fractions were characterised and we

52 4 Analytical research reports 51 Figure 3. Relative content of proteins, G12 and R5 reactive peptides and coeliac immunogenic pattern of the different barley beer fractions. Fractions were obtained in the process of separation of peptides by G12 mab immunodepletion quantified the relative content of proteins, G12 and R5 reactive species, and T-cell activation. As expected, material immunocaptured by G12 (peptides and proteins) comprised no more than 5% of the total protein content in the beer. However, these peptides were responsible for about 90% of the immunogenicity of the total beer. Strikingly, almost 80% of the reactivity of the R5 mab is located in the pool of peptides and proteins with poor immunogenic activity, as corroborated by the proliferative responses of T- cells and IFN-γ production by PBMCs of coeliac patients. Conclusion We have shown that analysing a beer with standard methods like ELISA R5 to grant it the gluten-free label might not fully guarantee the absence of potential damage to coeliac patients. There is experimental evidence that a better indicator of the potential immunogenicity is the reactivity to the -gliadin 33-mer A1 or G12, even if the 33- mer canonical sequence is not supposed to be present in barley. Other epitopes of the 33-mer are enough to sensitively detect GIP by G12/A1 in barley beers. In contrast, the presence of the preferred R5 epitope QQPFP in certain peptides of the Strong Ale 5, was not sufficient to detect those GIP that appeared detectable by HPLC-MS analysis. In general, the G12 immunomethods appear to be the most

53 52 Comparison of immunomethods for the analysis of gluten specific practical techniques described so far to assess the potential immunogenicity of barley beers. References 1. Anderson RP, Degano P, Godkin AJ, et al. In vivo antigen challenge in celiac disease identifies a single transglutaminase-modified peptide as the dominant A- gliadin T-cell epitope. Nat Med 2000; 6: Shan L, Molberg Ø, Parrot I, et al. Structural basis for gluten intolerance in celiac sprue. Science. 2002; 297: Tye-Din JA, Stewart JA, Dromey JA, et al. Comprehensive, quantitative mapping of T cell epitopes in gluten in celiac disease. Sci Transl Med 2010; 2: Real A, Comino I, Moreno Mde L, et al. Identification and in vitro reactivity of celiac immunoactive peptides in an apparent gluten-free beer. PLoS One 2014; 9:e Moreno Mde L, Muñoz-Suano A, López-Casado MÁ, et al. Selective capture of most celiac immunogenic peptides from hydrolyzed gluten proteins. Food Chem 2016; 205: Comino I, Real A, Moreno Mde L, et al. Immunological determination of gliadin 33-mer equivalent peptides in beers as a specific and practical analytical method to assess safety for celiac patients. J Sci Food Agric 2013; 4: Torgler C, Síglez MA, Vílchez F et al. Analytical tools to detect gluten immunotoxic fractions in food based on monoclonal antibodies raised against the gliadin 33-mer peptide. 24 th Proceedings of the WGPAT 2011.

54 4 Analytical research reports Pathogenesis of coeliac disease: complexes between transglutaminase and gluten peptides Barbara Lexhaller, Peter Koehler, Katharina A. Scherf Deutsche Forschungsanstalt für Lebensmittelchemie, Leibniz Institut, Freising, Germany Introduction Coeliac disease can be characterised by three features: (A) triggered by the ingestion of gluten, (B) presence of the genetic factor (HLA-DQ2 or DQ8), and (C) the generation of autoantibodies against tissue transglutaminase (TG2) [1]. After the ingestion of gluten, these proteins (gliadins, glutenins, hordeins, and secalins) are not sufficiently digested by human gastrointestinal enzymes due to their high proline and glutamine contents. These long peptides pass through the epithelial layer and first trigger the innate immune response. Intraepithelial lymphocytes activate defence mechanisms, which initiate apoptosis and are increase of epithelial permeability. Secondly, the gluten peptides are modified by TG2 that catalyses deamidation and transamidation. The modified peptides stimulate gluten-specific T-lymphocytes, which finally lead to the damage of the villi of the small intestine. Furthermore, antibodies are formed against gluten peptides, TG2 and gluten peptide-tg2-complexes [1-3]. TG2 plays a key role in the pathogenesis of coeliac disease. Firstly, it causes deamidation of specific glutamine residues to glutamic acid, which increases the immune response. It also initiates transamidation and formation of gluten peptide- TG2-complexes that lead to the formation of antibodies against them. TG2 is a Ca 2+ - dependent protein-glutamine γ-glutamyltransferase (EC ), which catalyses the formation of inter- and intramolecular N ε (γ-glutamyl)lysine bonds. The transfer of the acyl residue between the -carboxyamine group of glutamine as acyl donor and primary amines as acyl acceptors involves a two-step reaction mechanism. The three amino acids cysteine-277, histidine-335, and aspartic acid-358 of the active site of the enzyme are involved in this mechanism. According to the hypothetical model of hapten-carrier-like complexes these covalently bound gluten peptide-tg2- complexes should be responsible for the formation of anti-tg2 antibodies. However, the investigation of the structures of these gluten peptide-tg2-complexes is still at the beginning. Therefore, the aim of this study was to identify the binding sites between TG2 and peptides derived from all CD-active gluten protein types of wheat, rye, and barley.

55 54 Complexes between transglutaminase and gluten peptides Materials and methods Characterisation of microbial transglutaminase The microbial transglutaminase from Streptomyces mobaraensis (ABEnzymes, Darmstadt, Germany) was dissolved in formic acid (0.1%), filtered (0.45 µm) and measured by liquid chromatography with mass spectrometric detection (LC-MS (QTOF)). Furthermore, the microbial transglutaminase was characterised by the analysis of the tryptic peptides by LC-MS/MS (iontrap). For this purpose, the enzyme was incubated with trypsin in TRIS-HCl-buffer (0.1 mol/l; ph 7.8) for 24 h at 37 C. After purification with solid phase extraction, the hydrolysates were dried, dissolved again in formic acid (0.1%) and analysed by LC-MS/MS (iontrap). Identification of isopeptides For the reaction of microbial transglutaminase and a defined model peptide gli (LQLQPFPQPQ 65 LPYPQPQLPY) to peptide-enzyme-complexes, both were dissolved in TRIS-HCl-buffer (0.1 mol/l; ph 7.8; 2 mmol/l CaCl 2 ) and incubated for 2 h at 37 C. The peptide-enzyme-complexes were incubated with trypsin for 24 h at 37 C. After purification with solid phase extraction the hydrolysates were analysed by LC- MS/MS (iontrap). Results and discussion Characterisation of microbial transglutaminase Initially, the microbial transglutaminase (mtg) had to be characterised by molecular weight and by sequence analysis. The characterisation by molecular weight was carried out by LC-MS/MS (QTOF) with a high intensity. The identified molecular weight of the microbial transglutaminase was determined as 37,863.6 ± 0.5 (Fig. 1), which is comparable to the data (P81453) of the UniProt KB database. Also Kanaji et al. could identify the same molecular weight for microbial transglutaminase and showed the separation of signal- and propeptide during the MS measurement [4].

56 4 Analytical research reports 55 Figure 1. Mass spectrum of microbial transglutaminase. The spectrum corresponds to the average of scans of the base peak-chromatogram at min. The simulated maximum entropy peak is shown in the upper right corner Furthermore, the analysis of the tryptic peptides of mtg confirmed the characterisation and comparability with P Thirteen tryptic peptides were evenly distributed over the whole sequence, without the signal- and propeptide. Table 1. Tryptic peptides of microbial transglutaminase, their m/z ratio with charge state, the position in the UniProt database sequence and the score of the search with MASCOT-software ( 30). Tryptic peptide m/z (charge state) Position Score DSDDRVTPPAEPLDR (2 + ) AETVVNNYIR (2 + ) LAFASFDEDRFKNELK (3 + ) ESFDEEKGFQR (2 + ) ALENAHDESAYLDNLKK (2 + ) ELANGNDALRNEDAR (3 + ) SPFYSALR (2 + ) YGDPDAFRPAPGTGLVDMSR (3 + ) NWSEGYSDFDR (2 + ) SWNTAPDKVK (2 + )

57 56 Complexes between transglutaminase and gluten peptides Identification of isopeptides To identify the binding sites between mtg and the model peptide, the transglutaminase was first allowed to react with the peptide, the complexes were hydrolysed and these tryptic peptides were analysed with LC-MS/MS. In the second part, an analysis strategy for the identification of the isopeptides had to be developed. For this purpose, all theoretically possible combinations between a lysine residue (K) of the enzyme and a glutamine residue (Q) of the model peptide, their masses and their precursors (m/z) in the different charge states were calculated and theoretically fragmented. In the next step, the measured MS- and MS/MS-spectra were searched for the calculated masses of the precursors and fragments. For the identification of the binding Q, a data analysis strategy had to be developed to detect fragments which confirm the binding site. Initially, the spectra were searched for isopeptide bonds at Q 65, because Fleckenstein et al. (2004) already showed that this position is a binding site for TG2 [5]. Fig. 2 presents the isopeptide of the model peptide with the possible binding site (Q 65 ) and the tryptic peptide KWQQVYSHR of the transglutaminase. To confirm the position of the isopeptide bond at Q 65 the specified fragments b 10α or b 11α as well as b 9α, b 8α, y 11α or y 12α and y 10α had to be identified. At last, to confirm the identification of the whole isopeptide, 5 other fragments, e.g. b 5β or y 6β had to be identified. Figure 2. Strategy for identification of the binding Q in isopeptide bonds. Isopeptide (precursor m/z = (3 + )) of the model peptide and the tryptic peptide KWQQVYSHR of microbial transglutaminase (mtg) with the specified fragments for confirmation of the binding site The mass spectrum of the isopeptide of the model peptide gli and the tryptic peptide KWQQVYSHR of the microbial transglutaminase is presented in Fig. 3. Twenty-three fragments of the b- and y-series could be identified in the entire isopeptide and all signals had an adequate intensity. Another condition for the certain identification is to identify at least three consecutive fragments. With the detected fragments b 10α to b 14α and b 5β to b 8β as well as y 8α to y 10α and y 12α to y 14α this requirement was fulfilled. Also the conditions for the affirmation of the binding Q

58 4 Analytical research reports 57 were fulfilled by the identification of the specified fragments b 10α and b 11α as well as y 12α and y 10α. Figure 3. Mass spectrum of the isopeptide (m/z = (3 + )) of the model peptide gli and a tryptic peptide of the transglutaminase Until now, five tryptic peptides of mtg were identified, which form isopeptide bonds with the Q 65 of the model peptide gli Tab. 2 shows these tryptic peptides and their position in the transglutaminase sequence. Table 2. Identified tryptic peptides of the microbial transglutaminase, which bind to the model peptide gli at Q65, their position in the sequence and m/z ratio and the charges state of the formed isopeptides. Tryptic peptide Position m/z (charge state) KWQQVYSHR (3 + ) SWNTAPDK (3 + ) VAKESFDEEKGFQR (4 + ) NTPSFK (3 + ) NWSEGYSDFDRGAYVITFIPK (4 + )

59 58 Complexes between transglutaminase and gluten peptides Conclusion First, the characterisation of the microbial transglutaminase by molecular weight and sequence analysis was performed by two different types of LC-MS/MS. The results of the microbial transglutaminase used here were comparable with the data of the UniProt KB database (P81453). The preliminary experiments on the identification of isopeptides were focused on the development of a strategy, whereby first results were achieved. Until now, this strategy allowed the identification of five isopeptides with the binding site at Q 65 of the model peptide gli References 1. Schuppan D, Junker Y, Barisani D. Celiac disease: from pathogenesis to novel therapies. Gastroenterology 2009; 137: Kagnoff M. Celiac disease: pathogenesis of a model immunogenetic disease. J Clin Invest 2007; 117: Qiao SW, Iversen R, Ráki M et al. The adaptive immune response in celiac disease. Semin Immunopathol 2012; 34: Kanaji T, Ozaki H, Takao T et al. Primary structure of microbial transglutaminase from Streptoverticillium sp. strain. J Biol Chem 1993; 268: Fleckenstein B, Qiao SW, Larsen MR et al. Molecular characterization of covalent complexes between tissue transglutaminase and gliadin peptides. J Biol Chem 2004; 279:

60 4 Analytical research reports Potential of non-prolamin storage proteins in coeliac disease Gyöngyvér Gell 1, Gábor Veres 2, Ilma Rita Korponay-Szabó 3, Angéla Juhász 1 1 Department of Applied Genomics, Agricultural Institute, MTA Centre for Agricultural Research, Martonvásár, Hungary 2 First Department of Paediatrics, Semmelweis University of Medicine, Budapest, Hungary 3 Celiac Disease Centre, Pál Heim Children's Hospital, Department of Paediatrics, Budapest, Hungary Introduction Brachypodium distachyon is a small annual grass that belongs to the Pooideae subfamily of the grasses, and based on the recent phylogenetic analyses is the closest wild relative of wheat and barley. This wild grass with special biological properties (small size, rapid generation time and self-fertility) and genomic attributes (small genome (272Mbp), diploid accessions) is suitable for use as a model system of cereals. B. distachyon accession Bd21 offers many advantages, such as self-fertility, simple nutrient requirements and short lifecycle. Sequencing and annotation of the Bd21 genome were recently completed, making further functional proteomic studies feasible [1-3]. The main storage proteins of Bd21 are the 11S, 12S and 7S globulin type proteins similar to oat and rice. The prolamins, including the avenin-like proteins and the gliadin-like prolamins, represent less than 12% of the total protein content which is significantly lower compared to wheat or barley. Due to specific proteomic features this annual grass is a good model plant to investigate the toxic nature of non-prolamin seed storage proteins. 11S-12S globulins account for 70-80% of total seed protein content [4]. In our previous study, the published chromosome specific B. distachyon genome sequences and a seed specific cdna library data were used for sequencebased identification of proteins with regions identical to known coeliac diseasespecific epitopes [5]. These results have highlighted the presence of possible crossreactive epitope homologues to coeliac disease-related trigger molecules. Although Brachypodium is not considered for human nutrition, we took advantage of its use as a model species for the understanding whether abundant non-prolamin cereal seed proteins with linear epitope homologues play a role in the development of the humoral immune response and to help select other food sources suitable for a gluten-free diet. Materials and methods Serum samples from coeliac patients with known HLA-DQ haplotypes and positive for coeliac disease antibodies on gluten intake (n = 13, 8 females, 5 males), median age 5.7 years, range years), serum samples from coeliac patients adhering to

61 60 Non-prolamin storage proteins in coeliac disease a strict gluten-free diet (GFD) resulting in normalised antibodies (antitransglutaminase IgA < 10 U/l) and mucosal healing (n=3), from ten newly diagnosed Crohn s disease patients with ileocolon manifestation (median age 6.4) and from eight healthy control subjects were used for immunoblotting studies. In case of Bd21 total protein extracts, proteins were extracted with SDS buffer following the protocol of Dupont and co-workers [6] which extracted a greater percentage of protein from wheat flour than other methods and facilitated removal of starch. After the 2D gel electrophoresis (GE) the proteins were transferred to an ImmobilonP PVDF membrane and IgA-based immunoblots were carried out. Rice glutelin antibody coupled with anti-rabbit IgA as a secondary antibody was used in 2D Western blot analysis to confirm the presence of seed storage globulins [7]. Protein sequences identified based on the online nanolc-ms/ms analysis were retrieved from the UniProt database and were used for detailed epitope mapping analyses and protein characterisations. p-blast was used to find protein homologues in Poaceae. Coeliac disease-specific linear T-cell and B-cell epitopes were collected from the ProPepper database [8]. Epitope mapping was carried out using the motif search algorithm of the CLC Genomic Workbench (8.5.1). Results and discussion Brachypodium distachyon, a model plant of monocot species with low prolamin content was investigated to characterise immune reactivity against non-prolamin proteins in the seed. Altogether, 28 immune-reactive protein spots were analysed by online nanolc-ms/ms (Fig 1.). Antibody reactivity against Brachypodium proteins was detected in all coeliac disease patients and two of Crohn s disease patients. While positive IgA reactions of coeliac serum samples were detected against proteins from a wide range of molecular weight (approximately 15,000 to 65,000) and variable isoelectric points, the protein spots showing immune reactivity with Crohn s disease serum samples possessed an approximate molecular weight of 24,000. No proteins reacted when sera of healthy controls and sera of patients on a strict gluten-free diet were applied. Most of the spots were identified as 7S or 11S-12S type seed storage globulins. A few prolamin-type storage protein sequence hits were also identified as secondary or tertiary protein hits with similar sequence coverage values: gamma gliadin-like proteins, HMW glutenin-like proteins, and LMW type respectively. Some enzymes and proteins with non-storage function were identified in the 35,000 region, like glucose/ribitol dehydrogenase, aldo-keto reductase, xyloglucan endotransglucosylase/hydrolase and aspartic peptidase. The most significant globulin hits (I1GPS5, I1GMC8, I1HMK7, I1IPF2 I1HNH9) as well as the most frequently identified prolamin protein (I1HRM6) were subjected to in silico sequence analyses. Two adjacent cupin-1 domains characteristic for both 7S and 11S-12S seed storage globulins were found in all of the Brachypodium globulin hits

62 4 Analytical research reports 61 (Fig. 2). The identified epitope homologues represented peptides with polyq stretches and were positioned in two glutamine-rich regions of the protein. Additionally, a peptide with six residues (QPEQPF) was identified in the 11S seed storage globulin I1HNH9. This peptide was the deamidated version of a known immune reactive AGAspecific B-cell epitope QPQQPF (IEDB Epitope ID ) that gets deamidated during coeliac disease pathogenesis. This deamidated version represents one of the primary targets of serum deamidated gliadin peptide (DGP) antibodies in coeliac disease. Interestingly, none of the I1HNH9 Poaceae homologues contained this deamidated peptide. No epitope homologues were found in the metabolism-related proteins. Figure 1. Identification of coeliac disease-related proteins of Brachypodium distachyon Bd21 using anti-iga detection and patients blood sera. (A) 2D gel electrophoresis of total protein extract of inbred line Bd21. Proteins were separated on 3-10 ph IPG strips followed by separation on 12% acrylamide gels. Labelled protein spots represent immune-reactive proteins and were sent for online nanolc- MS/MS analyses. Molecular weight range is marked on the left-hand side. (B) and (C) Representative immunoblots using sera with IgA reactivity of therapy naïve coeliac disease patients, (B) HLA-DQ2, (C) HLA-DQ8

63 62 Non-prolamin storage proteins in coeliac disease When gluten-related known T-cell epitopes were mapped to the Brachypodium proteins, no known epitopes were found. However, a type-i diabetes-specific T-cell epitope, EEQLRELRRQ [9] was identified from I1GPS5 with 100% sequence identity at the position 281. To check for novel T-cell epitopes, MHC-II binding predictions were carried out from the main 7S, and 11S-12S globulin hits using HLA-DR3-DQ2 and HLA-DR4-DQ8 MHC-II haplotypes (Fig. 2.) [10]. Some previous studies have focused on the investigation of immune reactivity and toxic behaviour of non-gluten proteins of wheat related to coeliac disease [11-14]. Recently, Huebener and colleagues have analysed the possible involvement of non-gluten proteins as target antigens in coeliac disease-related humoral response [15]. Serine-protease inhibitors, alpha-amylase inhibitors, farinins and seed globulins have demonstrated a significant immune response. Additionally, 35% of coeliac disease patients sera showed reactivity against protein spots identified as seed globulins using the protein extract of Butte86 wheat [14]. Increased coeliac serum antibody reaction was also measured against cereal globulin extracts by Troncone et al. [13]. Although 7S and 11S-12S seed storage globulins both represent strongly conserved protein families with cupin-1 domains in cereals, our epitope analyses highlighted some remarkable differences between the protein families [10]. These differences indicate the presence of possible sub-classes with various immune-reactive potential. The amount of these unique globulin sub-classes can also be different in the grains of the different species, with a Figure 2. MHC II class T-cell epitope prediction of Brachypodium 7S and 11S-12S globulin proteins using HLA-DQ2 and -DQ8 alleles and IEDB analysis resource Consensus tool. Selection of predicted binders was carried out using the top 1% binders based on consensus percentile rank values. Predictions were calculated for each allele separately. Predicted epitopes are mapped to the protein sequences

64 4 Analytical research reports 63 significantly lower amount expressed in wheat and in cereals, where prolamins serve as major storage protein components. This fact partially explains why these proteins were overlooked compared to the most abundant prolamins in wheat, rye or barley. Our study confirmed that globulin-type cereal seed storage proteins are specifically related to coeliac disease, as patients suffering from other immunological inflammatory diseases, like Crohn s disease did not recognise these globulin-type cereal storage proteins. Adverse results of the immunoblot analyses with sera of coeliac patients on a gluten-free diet had also strengthened the assumption that seed storage globulins may act as secondary B-cell stimulants due their strong sequence homology to epitopes originated from the primary gluten triggers. In progressive stages of the disease, villous atrophy and increased gut permeability contribute to why these proteins can serve as cross-antigens. The recovered intestinal mucosa of the coeliac patient on a strict gluten-free diet better prevents the passage of ingested proteins and probably, in this way, the strong immune reactivity can be controlled. Conclusion In summary, our results indicate that both in coeliac disease and type-i diabetes MHC- II-presentation and B-cell response may be developed not only for prolamins, but also for seed storage globulins even in distant relatives of wheat, such as Brachypodium distachyon, having seed storage globulins similar to oat and rice. However, its seed storage proteins, especially globulins, belong to quite conserved proteins in plants, which when eaten, may cause some problems due to the presence of some B-cell epitope homologues and possible T-cell reactive peptides present in the globulin fraction. Therefore, such cereals would not be harmless food alternatives for coeliac patients. High-resolution 2D gel electrophoresis followed by immunoblotting and protein identification have proven that 7S and 11S-12S seed storage globulins may act as antigens for coeliac disease specific IgA antibodies. Storage globulins are only present as contaminants in wheat gluten; therefore they play a less significant role. Contrary to this, seed storage globulins are the main source of nutrient storage in cereals like rice, oat or Brachypodium. Despite the strongly conserved structure of 7S globulins, proteins like Glo3A in wheat and I1GPS5 in Brachypodium and some of the 11S-12S globulins represent a special class of seed globulins with an epitope-dense region between the two cupin-1 domains and therefore might represent a higher risk for coeliac disease patients. Our study draws attention on the presence of conserved seed storage protein families in various cereal species, such as wheat, oat, rice and Brachypodium. Although 7S and 11S-12S seed globulins are present in low amounts in the wheat grain, they represent major storage protein groups in species like oat or rice. Therefore the presence of some epitopes in highly conserved regions may be also characteristic on orthologues in other species. The level of the response to globulins may depend on the type of seed globulins and amount of proteins with immune responsive peptide content. It is also suggested to perform further investigations whether diets enriched in seed storage globulins (like rice or oat) inhibit sufficient

65 64 Non-prolamin storage proteins in coeliac disease healing, especially in patients with combined high risk to type-i diabetes and proven susceptibility to these proteins. Acknowledgement This project was supported by the European Union and co-financed by the European Social Fund (grant agreement no. TÁMOP A-11/1/KONV ), OTKA , OTKA K10088 and OTKA PD References 1. Ozdemir BS, Hernandez P, Filiz E, et al. Brachypodium genomics. Int J Plant Genomics 2008; 2008: Peraldi A, Beccari G, Steed A, et al. Brachypodium distachyon: a new pathosystem to study Fusarium head blight and other Fusarium diseases of wheat. BMC Plant Biol 2011; 11: Hands P, Drea S. A comparative view of grain development in Brachypodium distachyon. J Cereal Sci, 2012; 56: Larré C, Penninck S, Bouchet B, et al. Brachypodium distachyon grain: identification and subcellular localization of storage proteins. J Exp Bot 2010; 61(6): Juhász A, Gell G, Sebestyén E, et al. Brachypodium distachyon as a model for defining the allergen potential of non-prolamin proteins. Funct Integr Genomics 2012; 12: Dupont FM, Vensel WH, Tanaka CK, et al. Deciphering the complexities of the wheat flour proteome using quantitative two-dimensional electrophoresis, three proteases and tandem mass spectrometry. Proteome Sci 2011; 9 (10): Krishnan HB, Okita TW. Structural relationship among the rice glutelin polypeptides. Plant Physiol 1986; 81: Juhász A, Haraszi R, Maulis C, et al. ProPepper: a curated database for identification and analysis of peptide and immune-responsive epitope composition of cereal grain protein families. Database 2015; article ID bav100, doi: /database/bav Scott LJ, Mohlke KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 2007; 316 (5829): Gell G, Kovács K, Veres G, et al. Characterization of globulin storage proteins of a low prolamin cereal species in relation to celiac disease. Sci Rep 2017; 7: Stern M, Fischer K, Gruttner R. Immunofluorescent serum gliadin antibodies in children with coeliac disease and various malabsorptive disorders. II. Specificity

66 4 Analytical research reports 65 of gliadin antibodies: immunoglobulin classes, immunogenic properties of wheat protein fractions, and pathogenic significance of food antibodies in celiac disease. Eur J Pediatr 1979; 130(3): Kieffer M, Frazier PJ, Daniels NW, et al. Wheat gliadin fractions and other cereal antigens reactive with antibodies in the sera of celiac patients. Clin Exp Immunol 1982; 50(3): Troncone R, Auricchio S, De Vincenzi M, et al. An analysis of cereals that react with serum antibodies in patients with coeliac disease. J Pediatr Gastroenterol Nutr 1987; 6(3): Penttila IA, Devery JM, Gibson CE, et al. Cellular and humoral responses in coeliac disease. 1. Wheat protein fractions. Clin Chim Acta 1991; 204(1-3): Huebener S, Tanaka CK, Uhde M, et al. Specific nongluten proteins of wheat are novel target antigens in celiac disease humoral response. J Proteome Res 2015; 14(1):

67 66 Non-prolamin storage proteins in coeliac disease

68 4 Analytical research reports Preview of the Well on Wheat? (WoW) project Twan AHP America 1, Luud JWJ Gilissen 1, Marinus JM Smulders 1, Peter Shewry 2, Flip van Straaten 3, Daisy Jonkers 4, Fred Brouns 4 1 Wageningen University & Research, Wageningen, The Netherlands 2 Rothamsted Research, Harpenden, United Kingdom 3 Dutch Bakery Institute, Wageningen, The Netherlands 4 Maastricht University, Maastricht, The Netherlands Abstract The Well on Wheat (WoW) project aims to generate robust data on the effects of wheat-based food products on gastrointestinal function and metabolism. The first objective of the project is to obtain in-depth analytical data of the composition of whole meal obtained from bread wheat, spelt wheat and emmer wheat as well as the dough and the finally baked bread made thereof. The second objective is to study the effects of two alternative fermentation processes: yeast and sourdough fermentation, on compositional changes. Objective 1 and 2 will give insight in the overall effects of food processing on the (bio)chemical composition as defined by proteomics, carbohydrate analysis (carbohydrates, fibers, FODMAPs), phytate, selected micronutrients and pesticide residues. The third objective is to study the effects of consuming the various bread types (according to grain type and fermentation type) in individuals with irritable bowel syndrome (IBS), which will be monitored for effects on intestinal function and physiology, including e.g. faecal microbiota/metabolism, and using markers for gut permeability and inflammation as well as measuring subjective perceptions. The project will generate new scientific insights that will be translated into recommendations to food industries, health professionals and patient/consumer organisations. This project will be carried out in the framework of the Health Grain Forum and supported by the ICC (International Association for Cereal Science and Technology) and funded by private and public organisations. Introduction During the last decade, a significant movement to the adoption of gluten-free and wheat-free foods has developed in Western societies. The prevalence of wheat intolerance (coeliac disease) and wheat allergy are well known, being 1% and 0.2% of the general population, respectively. However, in the US, nearly 30% of the adult population has expressed a desire to reduce or eliminate wheat and/or gluten from their daily diet [1] while a recent questionnaire-based study in the Netherlands [2] showed that 6.2% of a cohort of 785 adults reported adverse symptoms after the ingestion of gluten-containing foods. The most widely reported intestinal symptoms were bloating, abdominal discomfort and flatulence, but extraintestinal symptoms were also

69 68 Preview of the Well on Wheat? (WoW) project mentioned such as fatigue and headache. Symptoms were generally experienced several days a week, starting mostly between one and six hours after consumption and lasting several hours. These self-reporting gluten sensitive individuals were mainly younger females ( 80%) living in urban regions with a trend of higher education levels (which confirms previous data of a UK study on self-reported gluten sensitivity [3]). Over one third of the reported symptoms met the consensus criteria for a positive diagnosis, the Rome III criteria for IBS, which have been established due to the absence of reliable biomarkers and specific laboratory tests [4]. The reasons why so many people feel more comfortable on a gluten-free diet may extend beyond the food itself. Several popular books [5-7] and many statements on social media have promoted gluten-free ( Palaeolithic ) diets, suggesting that wheat consumption has adverse health effects leading to various chronic diseases. Furthermore, it is often claimed that products made from modern bread wheat varieties have negative health effects, but not foods made from so-called ancient wheats such as spelt (which is closely related to modern bread wheat) and emmer (which is more closely related to modern pasta wheat), which are generally cultivated under organic conditions. These messages are, however, in contradiction to ample scientific data that have demonstrated significant health-promoting effects of whole grain consumption [8-12]. Despite these proven health benefits, the negative messages have resulted in a significant decline in the consumption of breads and other wheat products in Western countries. In this context, IBS has often been considered by the patients themselves to be associated with food and especially wheat consumption. IBS is the most commonly diagnosed functional gastrointestinal (GI) disorder with a prevalence of 10-20% worldwide, predominantly among women [13]. Structural abnormalities and tissue damage are generally absent, but psychiatric co-morbidity is often reported, indicating a psychosomatic component in a subgroup of these patients. Although several factors have been associated with IBS, including e.g. microbial perturbations, altered permeability, motility and visceroperception, the exact pathophysiology is not yet clear. Also markers for mucosal immune activation and inflammatory responses have been reported in a subset of IBS patients that may disappear after elimination of wheat/gluten from the diet [14,15]. This condition is often referred to as non-celiac wheat sensitivity (NCWS) or non-celiac gluten sensitivity (NCGS) [16]. Dietary factors such as FODMAPs (fermentable, oligo-, di-, monosaccharides and polyols) have been recognised as triggers for symptoms in some subjects, by providing substrates for colonic fermentation [16 and refs therein, 17]. It has also been reported that replacing a bread wheat-based diet by whole grain products from ancient wheats such as spelt, has benefits for IBS patients [18,19]. In addition to gluten and FODMAPs, the presence of relatively high quantities of amylase-trypsin inhibitors (ATIs) in bread wheat has also been suggested as a potential IBS causing factor [20,21]. Direct comparative data about the effects of foods obtained from different

70 4 Analytical research reports 69 wheat types and their possible contribution to the pathophysiology of NCWS are, however, still lacking. Here we propose a research strategy to address this issue. Project design The WoW project will study the effect of different grains in IBS patients to provide information on the wheat- and disease-related issues at three levels: (1) The biochemical composition of wheat grains and changes during processing steps (milling, fermentation, baking) into consumable food products (bread); (2) The impact of bread consumption on well-being and GI symptoms, gut permeability, immune function and the microbiome; and (3) The impact of the opinions and perception of consumers/patients on wheat consumption or avoidance regarding gastrointestinal symptoms and well-being. The project will be managed by the academic and funding partners in a contractually agreed pre-competitive manner. Materials and methods Grains. Grains from bread wheat (Triticum aestivum) (representing current bread products), spelt wheat (T. aestivum ssp spelta) and emmer wheat (T. dicoccum) (both representing ancient wheat species) obtained commercially will be analysed for biochemically for proteins using proteomics (detection of gluten, globulins, albumins, ATIs, lectins, indigestible peptides), fibre (including fructans and other FODMAPs), phytate, phenolics, minerals (such as zinc and magnesium), at the level of flours, fermented (yeast and sourdough) doughs, and breads. Cohort and intervention groups. We aim at measuring the effects of wheat consumption in IBS patients, recruited from a large cohort of well-characterised IBS patients [22] that has been established at Maastricht University Medical Centre. Three groups will be used in the intervention study, including successively: a running-in period (1 week), a free-from diet (2 weeks), a yeast or sourdough bread food challenge (2 weeks), a free-from wash-out diet (2 weeks) and a sourdough or yeast bread food challenge (2 weeks). It should be noted that the first and the second challenge are reversed regarding the yeast and the sourdough breads. The three groups will differ in their challenge: the groups 1, 2 and 3 will be challenged blinded with yeast and sourdough bread from either bread wheat, spelt wheat or emmer wheat. Sampling human materials. At each step in the challenge sequence, patient samples will be taken from (1) the stool to analyse microbiota composition and metabolites from bacterial protein and carbohydrate fermentation ((i.e. short chain fatty acids, branched chain fatty acids, etc.); (2) breath metabolome to identify volatile organic compounds reflecting host and microbial metabolism; (3) blood to determine alkylresorcinols, inflammation markers (C-reactive protein and cytokines); zonulin; and (4) urine sugar ratios as proxy for gut permeability. Furthermore, validated scores will be applied to measure wellbeing and GI symptoms.

71 70 Preview of the Well on Wheat? (WoW) project Yeast versus sourdough fermentation. Significant differences are expected in the biochemical composition after yeast fermentation as compared to sourdough fermentation [23]. If the results are not significant, the intervention schedule will be adapted accordingly. Nocebo effects. In healthy consumers, nocebo effects related to wheat/gluten avoidance will be determined through a food challenge with a single bread type that will be differently labelled and offered in four categories of emotional perceptivity and acceptability. Ethics. Before starting, the project will be evaluated, commented and approved by a Medical-Ethical Committee. Wheat cultivation. In an extension to the WoW project, the various wheat types (see Grains above) will be compared after growth under different conditions (organic vs standard) to determine effects of environment on composition. This data will may help to explain possible differences, between the grain types obtained from different European countries and cultivation practices. Partners and Sponsors The project proposal has been initiated by Maastricht University and further elaborated together with Wageningen University & Research, the Dutch Bakery Centre (all from The Netherlands) and Rothamsted Research (UK). Most research partner organizations are members of Health Grain Forum (HGF) and the project fits into the activities of the HGF working group on Cereals and health and has been included in the general HGF programme. The International Association for Cereal Science and Technology (ICC; Austria) will serve as financial administrative partner for the following sponsoring entities: AB-Mauri Bakery Ingredients, Made, Netherlands CSM Innovation Bakery Center, Bingen, Germany CYMMIT, Texcoco, Mexico DSM Food Specialties, Delft, Netherlands Fazer Bakeries, Helsinki, Finland ICC- Intl. Association for Cereal Science and Technology, Vienna, Austria IWGA- Intl. Wheat Gluten Association, Kansas, USA Lantmännen EK, Stockholm, Sweden Mondelez, Saclay, France Dutch Bakery Center, Wageningen, Netherlands Nutrition et Sante, Revel, France Puratos BV, Groot Bijgaarden, Belgium

72 4 Analytical research reports 71 Sonneveld Group BV, Papendrecht, Nederlands, Zeelandia Zierikzee, Netherlands Baking Industry Research Trust Howick, Auckland, New Zealand Health Grain Forum, Vienna The project is in part publicly funded by the Dutch Topsector Agri&Food. The sponsoring organisations have neither a role in the design and execution of the project, nor in the collection, analyses, interpretation and publication of the data. Expected outcomes The project will generate comparative data on the biochemical composition of grains of bread wheat, spelt and emmer, with a major focus on those compounds expected to have positive or negative effects on health, such as carbohydrates (starch, fibre, FODMAPs), proteins (gluten, CD-immunogenic gluten peptides, albumins, globulins, lectins, ATIs), phenolic compounds, phytate, and minerals (Zn; Mg). In an extension of the project, biochemical analyses will be carried out on grains grown under different conditions. After milling, breads will be made using yeast fermentation and sourdough fermentation and the compositions of the doughs and flours compared. A great challenge is the production of breads from flours of the different grain types that are visually and organoleptically similar, so that they can be used in the double-blind food challenges. Administration of the baked products to patients with IBS (i.c. NCWS) will reveal any effects on the aetiology of non-celiac wheat sensitivity. The project will also provide insight into the occurrence of nocebo effects by collecting data obtained about post-consumption gastrointestinal symptoms from a group of healthy volunteers that prefer to avoid gluten. The results will be published in international scientific journals. New scientific insights will be translated into recommendations to wheat-processing industries, governmental regulatory bodies, health professionals, patients and consumers, and will underpin innovation in the production of wheat-based foods. Acknowledgements Here, we would like to mention the names and affiliation of the other scientific cooperators: Koen Venema, Frederik-Jan van Schooten, John Penders and Rob Markus (Maastricht University), Petra Kuiper and Zsuzsan Proos (NBC), Hetty Busink-van den Broeck, Ingrid van der Meer, Ruud Timmer (Wageningen University & Research). Thanks are due to the sponsors for their financial support. The project will be partly financially supported by the Dutch Topsector AgriFood (TKI 1601P01). Rothamsted

73 72 Preview of the Well on Wheat? (WoW) project Research receives grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) of the UK. References 1. NPD Monitor: 2. Van Gils T, Nijeboer P, IJssennagger CE, et al. Prevalence and characterization of self-reported gluten sensitivity in The Netherlands. Nutrients 2016; 8: 714; doi: /nu Aziz I, Lewis NR, Hadjivassiliou M, et al. A UK study assessing the population prevalence of self-reported gluten sensitivity and referral characteristics to secondary care. Eur J Gatroenterol Hepatol 2014; 26: Drossman DA. The functional gastrointestinal disorders and the Rome III process. Gastroenterology 2006; 130: Davis W. Wheat Belly. Broadhead Ass 2011; 292 pp. 6. Perlmutter D. Grain Brain. Hodder & Stoughton 2014; 336 pp. 7. Verburg K. De Voedselzandloper. Uitgeverij Bert Bakker 2012; 368 pp. 8. Wu H, Flint AJ, Qibin Q, et al. Association between dietary whole grain intake and risk of mortality. JAMA Intern Med 2015; 173: Huang T, Xu A, Lee A, et al. Consumption of whole grains and cereal fibre and total and cause-specific mortality: prospective analysis of 367,442 individuals. BMC Med 2015; 13: 59; doi: /s Aune D, Keum N, Giovannucci E, et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies. BMJ 2016; 353: i2716; doi: /bmj.i Benisi-Kohansal S, Saneei P, Salehi-Marzijarani M, et al. Whole-grain intake and mortality from all causes, cardiovascular disease, and cancer: a systematic review and dose-response meta-analysis of prospective cohort studies. Adv Nutr 2016; 7: ; doi: /an Chen G-C, Tong X, Xu J-Y, et al. Whole-grain intake and total, cardiovascular, and cancer mortality: a systematic review and meta-analysis of prospective studies. Am J Clin Nutr 2016; 104: Canavan C, West J, Card T. The epidemiology of irritable bowel syndrome. Clin Epidemiol 2014; 6: Uhde M, Ajamian M, Caio G, et al. Intestinal cell damage and systemic immune activation in individuals reporting sensitivity to wheat in the absence of coeliac disease. Gut 2016; 65: ; doi: /gutjnl

74 4 Analytical research reports Caio G, Volta U, Tovoli U, et al. Effect of gluten free diet on immune response to gliadin in patients with non-celiac gluten sensitivity. BMC Gastroenterology 2014; 14: El-Salhy M, Hatlebakk JG, Gilja OH et al. The relation between celiac disease, nonceliac gluten sensitivity and irritable bowel syndrome. Nutrition Journal 2015; 14: Henström M, D Amato M. Genetics of irritable bowel syndrome. Mol Cell Pediatr 2016; 3: 7; doi: /s Sofi F, Whittaker A, Cesari F, et al. Characterization of Khorasan wheat (Kamut) and impact of a replacement diet on cardiovascular risk factors: cross-over dietary intervention study. Eur J Clin Nutr 2013; 67: Sofi F, Whittaker A, Gori AM, et al. Effect of Triticum turgidum subsp. Turanicum wheat on irritable bowel syndrome: a double-blinded randomised dietary intervention trial. Brit J Nutr 2014; 111: Schuppan D, Zevallos V. Wheat amylase trypsin inhibitors as nutritional activators of innate immunity. Dig Dis 2015; 33: Zevallos VF, Raker V, Tenzer S, et al. Nutritional wheat amylase-trypsin inhibitors promote intestinal inflammation via activation of myeloid cells. Gastroenterology 2017; DOI: /j.gastro Mujagic Z, Tigchelaar EF, Zhernakova A, et al. A novel biomarker panel for irritable bowel syndrome and the application in the general population. Sci Rep 2016; 6: doi: /srep Costabile A, Santarelli S, Claus S, et al. Effect of breadmaking process on in vitro gut microbiota parameters in irritable bowel syndrome PloS One 2014; 9: e doi: /journal.pone

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76 5 Clinical research reports 75 5 Clinical research reports 5.1 Oats in the diet of children with coeliac disease: a double-blind, randomised, placebo-controlled multicenter study Tiziana Galeazzi 1, Simona Gatti 1 Nicole Caporelli 1, Elena Lionetti 1, Ruggero Francavilla 2, Maria Barbato 3, Paola Roggero 4, Basilio Malamisura 5, Giuseppe Iacono 6, Andrea Budelli 7, Rosaria Gesuita 8, Carlo Catassi 1 1 Department of Pediatrics, Università Politecnica delle Marche, Ancona, Italy 2 Interdisciplinary Department of Medicine, University of Bari, Bari, Italy 3 Department of Pediatrics, Sapienza University, Rome, Italy 4 Neonatal Intensive Care Unit, Department of Clinical Sciences and Community Health, IRCCS Ca Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy 5 Department of Pediatrics, S. Maria dell Olmo Hospital, Cava de Tirreni, Salerno, Italy 6 Pediatric Gastroenterology Unit, G. Di Cristina Children Hospital, Palermo, Italy 7 R&D Heinz Italia S.p.a., Latina, Italy 8 Department of Epidemiology, Biostatistics, Università Politecnica delle Marche, Ancona, Italy Introduction Coeliac disease (CD) is an inherited autoimmune condition triggered in genetically susceptible individuals by amino acid sequences within the prolamin fraction of ingested wheat (gliadins), barley (hordeins) and rye (secaline). At present, the only treatment for this condition is the lifelong complete withdrawal of gluten from the diet [1]. Strict adherence to a gluten-free diet (GFD) is required to control the symptoms of CD and to prevent the autoimmune and neoplastic complications associated with this condition [2]. However, full compliance with a GFD heavily affects dietary choice and the quality of life. Although the quality of gluten-free food has significantly improved in the last decades, some problems still remain partially unresolved, in particular the lower technological performance of gluten-free cereals [3]. On this basis, the inclusion of oats in the GFD could be of great value. Oats are a good source of fibres and, in particular, of vitamins and minerals, and beta-glucans, which are healthy compounds that reduce LDL-cholesterol and the glycemic index of foodstuff [4,5]. Moreover, the inclusion of oats unquestionably improves the

77 76 Oats in the diet of children with coeliac disease: nutritional value and increases the palatability of gluten-free products, while expanding food choices and ultimately improving the quality of life for people with CD [6]. Although oats are included among the gluten-free ingredients (gluten content does not exceed 20 parts per million -ppm-) by European Commission Regulation No. 41/2009 [7] the safety of oats in CD is still a matter of debate. Some clinical trials have concluded that oats are well tolerated by CD patients on a GFD, but early studies found that some patients consuming oats as part of a GFD suffered an intestinal inflammation similar to that in untreated coeliac patients [8]. Previous studies were limited by small sample sizes or short follow-up periods and to the best of our knowledge there has been only one randomised placebo-controlled clinical trial. Moreover, oats is not a staple food in the diet of Mediterranean populations. This is probably the main reason why an oats resurrection in the GFD has not raised immediate interest in Southern European countries. Therefore, we aimed to evaluate in a large randomised, double-blind, cross sectional placebo-controlled multicenter clinical trial the clinical, serological and mucosal safety and the acceptance of gluten-free oat-based products from selected oat varieties in the diet of Italian children with CD. Clinical monitoring during the study was based on: a) score of intestinal symptoms; b) serological CD markers (TG-IgA, AGA-IgA, antiavenin) c) mucosal parameters integrity monitored by double sugars intestinal permeability test (IPT). Material and methods 306 children aged 4-14 years with biopsy-proven diagnosis of CD, on a GFD for at least 2 years, were recruited at 8 Pediatric Gastroenterology centres in Italy (Ancona, Bari, Bolzano, Catania, Monza, Palermo, Roma, Cava de Tirreni) between 2008 and Patients who (1) have chronic conditions, including type 1 diabetes or inflammatory bowel disease, or (2) did not adhere to the GFD as demonstrated by elevation of serological markers at enrollment, were excluded. Children were assigned on the basis of a stratified randomization to one of two groups: those assigned to group A received 6 months of diet A, 3 months of standard GFD as a wash out period, and 6 months of diet B; those assigned to group B received 6 months of diet B, 3 months of standard GFD as a wash out period, and 6 months of diet A (Fig. 1).

78 5 Clinical research reports 77 A Wash-out A Children with biopsy-proven CD diagnosis on GFD for>2 years ( ) R T0 * (B1) T6 * T9 * (B2) T15 * B Figure 1. Study cross-over design Wash-out B A and B diets included gluten-free products (flour, pasta, biscuits, cakes and crispy toast) with either purified oats or placebo, that were identical in form, and colour, and were both provided by a company leader in gluten-free production in Italy. The minimum oat intake required (calculated as 1 g/kg/day) was 15 g/day for children aged 3-6 years, 25 g/day for children aged 7-10 years and 40 g/day for children aged years. The oat varieties used were specially grown, milled and packaged to avoid any cross-contamination with gluten-containing cereals or food. Gluten contamination of used oats was measured by Ridascreen ELISA test. Clinical [Body Mass Index (BMI), class of BMI, Gastrointestinal Symptoms Rating Scale (GSRS) score], serological [IgA anti-transglutaminase antibodies, IgG antideamidated gliadin peptides (AGA) and IgA anti-avenin] and intestinal permeability test (IPT) data were measured at basal (B1, recruitment) and after six months of diet A or B in the first period (T6), after three months of wash-out at the beginning of the second period as a second basal point (B2) and after six months of diet A or B (T15). At each time point of follow-up the daily intake of oat was assessed by means of a three-day diary and symptoms and/or side effects related to the ingestion of the products under investigation was promptly recorded. Statistical analysis Sample size was estimated using intestinal permeability test (IPT) as primary response variable and considering a clinical difference between the two diets of 0.01 as minimum. Since the resulting data was not normally distributed, a non parametric approach was used for all statistical analyses. For descriptive purposes, absolute variations in clinical and anthropometric variables between T6 and B1 and T15 and B2, respectively in the first and in the second period of treatment, were calculated and graphically represented by boxplots.

79 78 Oats in the diet of children with coeliac disease: Ninety-five percent confidence intervals (95% CI) for median values were calculated and comparisons between diets groups in each treatment period were performed using Wilcoxon rank sum test. A positive variation indicated an increase in the variable, that was considered statistically significant when 95% CI did not contain zero value. First and second carry-over effect (θ, λ) and direct treatment effect (τ) were evaluated by a non-parametric statistical approach using medians as summary statistic. Confidence intervals for each effect were estimated using a probability of 0.90 for the first two (θ, λ) and 0.95 for τ. A probability of 0.05 was chosen to assess the statistical significance. Results and discussion After the exclusion of 129 patients who dropped out, the analysed cohort included 177 children (79 in group A and 98 in group B). There were 124 girls (70%) and the median age of the cohort was 8.9 years (range 6.9 to 11.2). Table 1 shows the patients main anthropometric and clinical characteristics at the first basal. No significant Table 1. Subjects' anthropometric and clinical characteristics at basal according to treatment groups. M=males, F=females, IQR=interquartile range. Groups [n (%)] AB (n=79) BA (n=98) p Gender Males 22 (27.8) 31 (31.6) Female 57 (72.2) 67 (68.4) Biopsy [ n (%)] 1 1 (1.4) 2 (2.5) 0.647* 2 2 (2.9) 1 (1.2) 3A 9 (13) 7 (8.6) 3B 27 (39.1) 27 (33.3) 3C 30 (43.5) 44 (54.3) Chi-square test; *Fisher exact test Median [IQR] AB BA p Age (years) 8.9 (6.9 ; 11.25) 9.3 (6.925 ; 12) Age at diagnosis (years) (2.145 ; 6.522) (2.927 ; 6.49) BMI (kg/m 2 ) 16.7 (15.35 ; 19.55) 18.2 (15.85 ; 20.48) BMI percentile 60 (35.5 ; 87) 69.5 (42.5 ; 91.75) GRSRS Score 2 (0 ; 4.5) 2 (0 ; 4) AgaIg 4.6 (2.3 ; 8.13) 5.6 (2.55 ; 8.9) TTGIgA 4.31 (2.1 ; 7.5) 5.1 (2.55 ; 7.8) TPI (0.029 ; 0.082) ( ; ) Anti-avenin (0.048 ; ) (0.05 ; 0.07) p-values refer to Wilcoxon rank sum test; IQR: 1st-3rd quartile

80 5 Clinical research reports 79 differences were found between the two groups, so it can be confirmed that randomization worked well. No significant differences were found between the two groups in the two treatment periods both for clinical parameters and serological parameters, neither for the mucosal parameteres as reported in Fig. 2, 3 and 4, respectively. BMI GSRS BMI (kg/mq) M - BL 15M - 9M GSRS M - BL 15M - 9M AB BA AB BA Aga Ig G AB BA AB BA Figure 2. Absolute variation in the two treatment periods according to groups in the clinical parameters BMI, BMI class and GSRS TTG Ig A Anti-avenina TTG Ig A M - BL 15M - 9M Aga Ig G M - BL 15M - 9M Anti-avenina M - BL 15M - 9M AB BA AB BA AB BA AB BA AB BA AB BA Figure 3. Absolute variation in the two treatment periods according to groups in the serological parameters TTG, IgA, Aga IgG, anti-avenin) TPI TPI M - BL 15M - 9M AB BA AB BA Figure 4. Absolute variation in the two treatment periods according to groups in the mucosal parameters (intestinal permeability, TPI)

81 80 Oats in the diet of children with coeliac disease: Table 2. Differences in clinical, serological and mucosal parameters during the two diet periods. Median (95%CI) 1 st -3 rd quartiles BMI BMI Class GRSR Score Aga Ig A Aga Ig G TTG Ig A TPI Antiavenin 1 period (T6-B1) 2 period (T15-B2) AB BA p AB BA p 0.4 (0.19; 0.61) 1 (-0.87; 2.87) 0 (-0.36; 0.36) 0.15 (-0.48; 0.78) 0.5 (-0.27; 1.27) (-0.54; 0.46) 0 ( ; ) 0 ( ; ) 0.4 (0.22; 0.58) 0.5 (-0.46; 1.46) -0.5 (-0.82; -0.18) 0.3 (-0.35; 0.95) -0.2 (-1.12; 0.72) 0.1 (-0.47; 0.67) 0 ( ; ) (-0.002; 0) (0.01; 0.39) 0 (-1.6; 1.6) 0 (-0.18; 0.18) 0.8 (0.17; 1.43) 0.3 (-0.62; 1.22) 0.2 (-0.32; 0.72) 0 (-0.01; 0.02) ( ; ) 0.3 (0.11; 0.49) 0 (-1.12; 1.12) 0 (-0.16; 0.16) -0.1 (-0.99; 0.79) (-0.87; 0.09) 0.45 (-0.23; 1.13) (-0.02; 0) (0; 0.002) Table 3. Results of crossover analysis between the two study groups. Median 1st-order carryover effect interaction Direct-by-period (1- /2 %CI) Direct treatment effect BMI (-0.05; 0.20) 0.05 (-0.15; 0.20) -0.5 (-0.12; 0) BMI Class 0.50 (-1.0; 1.50) 0.50 (-1.0; 2.0) (-1.0; 0.25) GRSR Score 0 (0; 0) 0 (-0.5; 0) 0 (-2.5; 0) Aga Ig A 0.29 (-0.35; 0.90) 0.14 (-0.70; 1.05) (-0.50; 0.25) Aga Ig G 0.29 (-0.35; 0.90) 0.15 (-0.70; 1.05) (-0.50; 0.25) TTG Ig A 0.4 (-0.05; 0.95) 0.30 (-0.25; 0.80) (-0.25; 0.23) IPT (-0.01;0.01) (-0.014; 0.007) ( ; ) Table 3 shows the results of crossover analysis; differences between the two groups in the variables of interest were summarised using medians and the first order carry-over effect, direct-by-period interaction, and a direct treatment effect according to the diet sequences AB, BA was evaluated by means of confidence intervals. A positive sign in

82 5 Clinical research reports 81 the direct treatment effect estimates indicated that treatment B was associated with the higher average of the variable. Differences in treatment carry-over at the time of the second baseline measurements (θ) and differences in treatment carry-over at the time of the second treatment measurement (λ) and direct treatment effect (τ) were found not statistically significant for all clinical, serological and mucosal variables studied. The upper limit of the 95% confidence interval of IPT direct treatment effect was found lower than the highest difference considered clinically relevant (0.01). These data confirm that this clinical trial is a study of non-inferiority, so an oatsenriched diet did not cause any modifications in coeliac children. There is no difference in treatment A with respect to treatment B. Conclusion In a large group of CD children, we found that the prolonged daily intake of a considerable amount of pure oats did not cause any significant change in terms of clinical symptoms, serological parameters and intestinal permeability. Coeliac disease children can safely add pure oats to their GFD. The inclusion of oats in the GFD would be beneficial, as they provide a good source of fibres, have a higher satiety value than other cereals, add texture and flavor to baked goods and could increase compliance with a GFD by providing patients with more alternatives. Disclosure of interest: All authors have conflict of interest with Heinz Company s.r.l. References 1. Rashtak S, Murray JA. Review article: coeliac disease, new approaches to therapy. Aliment Pharmacol Ther 2012; 35: Silano M, Volta U, Mecchia AM, et al. Delayed diagnosis of coeliac disease increases cancer risk. BMC Gastroenterol 2007; 9: De la Hera E, Talegon M, Caballero P, et al. Influence of maize flour particle size on gluten-free breadmaking. J Sci Food Agric 2013; 93: Wolover TM, Tosh SM, Gibbs AL, et al. Physicochemical properties of oat betaglucan influence its ability to reduce serum LDL cholesterol in humans: a randomized clinical trial. Am J Clin Nutr 2010; 92: Granfeldt Y, Nyberg L, Bjorck I. Muesli with 4 gram oat beta-glucans lower glucose and insulin responses after a bread meal in healthy subjects. Eur J Clin Nutr 2008; 62: Rashid M, Butzner D, Burrows V, et al. Consumption of pure oats by individuals with celiac disease: a position statement by the Canadian Celiac Association. Can J Gastroenterol 2007; 21:

83 82 Oats in the diet of children with coeliac disease: 7. Commission Regulation n.41/2009 concerning the composition and labelling of foodstuff suitable for people intolerant to gluten. Official Journal of the European Union dated , L16/3. 8. Silano M, Pozo EP, Uberti F, et al. Diversity of oat varieties in eliciting the early inflammatory events in celiac disease. Eur J Nutr 2014; 53:

84 5 Clinical research reports A study of morphological and immunological responses to a 14 day gluten challenge in adults with treated coeliac disease Vikas K. Sarna 1,2, Gry I. Skodje 2,3, Henrik M. Reims 4, Louise F. Risnes 1,5, Shiva D. Koirala 1,5, Ludvig M. Sollid 1,2,5, Knut E.A. Lundin 2,5,6 1 Department of Immunology and Transfusion Medicine, Oslo University Hospital, Norway 2 K G Jebsen Coeliac Disease Research Centre, University of Oslo, Norway 3 Division of Cancer Medicine, Oslo University Hospital, Norway 4 Department of Pathology, Oslo University Hospital, Norway 5 Centre for Immune Regulation, University of Oslo, Norway 6 Department of Gastroenterology, Oslo University Hospital, Norway Introduction Coeliac disease (CD) is a gluten-induced enteropathy [1]. The treatment is to exclude gluten completely from the diet, whereupon the derangement of the gut and the serum antibodies normalise. The clear association to distinct HLA-types has also shown the central role of T cells in the pathogenesis of CD [2]. Non-coeliac gluten sensitivity is defined as a gluten-induced disease with similar symptoms as CD, but without the typical findings in the gut and in the blood [3]. The prevalence of this condition may be higher than CD in many countries [4], leading to an increased awareness of gluten-induced disease in the population and a significant number of people eating a self-prescribed gluten-free diet without a proper diagnosis. A gluten challenge is performed when the patient has started on a gluten-free diet without proper diagnosis. According to guidelines [5,6], the recommended dose of gluten should be at least 3 grams daily, and the duration should be at least 8 weeks, or 2 weeks in the case of strong gluten-related symptoms. In this study we seek to evaluate different response parameters to a 14 day gluten challenge in adults with treated coeliac disease. Materials and methods We included twenty adults (Fig. 1) with treated coeliac disease for a two week gluten challenge. The participants were on a gluten-free diet, had normal duodenal biopsies and normal anti-transglutaminase IgA titers prior to challenge. Challenge was performed with a low-fodmap (fermentable oligo-, di-, monosaccharides and polyols) muesli bar containing 5.7 grams of gluten, taken once daily (Fig. 2). We took duodenal biopsies at the end of challenge. Blood was drawn at several time points. We

85 84 Morphological and immunological responses to a gluten challenge used HLA-gliadin-complexes (tetramers) linked to a fluorochrome, along with several monoclonal antibodies to characterise gluten-specific T cells in blood in a flow cytometer. Symptoms and quality of life parameters were scored by the use of GSRS- IBS, visual analogue scales and SF-36. Serum samples from the first day of challenge was collected at baseline, and then every second hour until 6 hours after the first dose of gluten to look for cytokine changes during the initial exposure. Fecal samples were collected at several time points during the study to characterise the microbiota and gluten associated changes herein. The study is approved by the regional ethical committee of South-East Norway (ref. 2013/1237) and registered at clinicaltrials.gov (NCT ). Assessed for eligibility (n=78) Excluded (n=58) Not meeting inclusion criteria (n=18) Declined to participate (n=35) Other reasons (n=5) Included (n=20) Figure 1. Flowchart showing the number of individuals assessed for eligibility, excluded and included in the study Figure 2. Timeline showing the course of the study Results and discussion The manuscript is in preparation and the data are still unpublished. We therefore choose not to present the results here. References 1. Sollid LM, Jabri B. Triggers and drivers of autoimmunity: lessons from coeliac disease. Nat Rev Immunol 2013; 13(4):

86 5 Clinical research reports Lundin KEA, Scott H, Hansen T, et al. Gliadin-specific, HLA-DQ(alpha 1*0501,beta 1*0201) restricted T cells isolated from the small intestinal mucosa of celiac disease patients. J Exp Med 1993; 178(1): Ludvigsson JF, Leffler DA, Bai JC, et al. The Oslo definitions for coeliac disease and related terms. Gut 2013; 62(1): Lundin KEA. Non-celiac gluten sensitivity - why worry? BMC Med 2014; 12: Rubio-Tapia A, Hill ID, Kelly CP, et al. ACG clinical guidelines: diagnosis and management of celiac disease. Am J Gastroenterol 2013; 108(5): ; quiz Ludvigsson JF, Bai JC, Biagi F, et al. Diagnosis and management of adult coeliac disease: guidelines from the British Society of Gastroenterology. Gut 2014; 63(8):

87 86 Morphological and immunological responses to a gluten challenge

88 5 Clinical research reports A double-blind placebo-controlled cross-over challenge with gluten and fructans in individuals with self-reported gluten sensitivity Gry I. Skodje 1,2, Vikas K. Sarna 2,3, Ingunn H. Minelle 4, Kjersti L. Rolfsen 4, Jane G. Muir 5, Peter R. Gibson 5, Marit B. Veierød 4,6, Christine Henriksen 2,4, Knut EA. Lundin 2,3,7 1 Divison of Cancer Medicine, Oslo University Hospital, Oslo, Norway 2 K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Norway 3 Faculty of Medicine, University of Oslo, Norway 4 Department of Nutrition, Institute for Basic Medical Sciences, University of Oslo, Norway 5 Department of Gastroenterology, Monash University and Alfred Hospital, Melbourne, Victoria, Australia 6 Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Norway 7 Department of Gastroenterology, Oslo University Hospital, Oslo, Norway Introduction Non-coeliac gluten sensitivity (NCGS) is a term within gluten-related disorders that has been applied for the condition where persons report symptom relief on a glutenfree diet in absence of coeliac disease and wheat allergy [1]. An important characteristic for the group is the experience of symptoms after intake of glutencontaining cereals, but the role of gluten as symptom inducer is questioned. There are no reliable diagnostic biomarkers for NCGS, but a standardised blinded placebocontrolled gluten challenge is proposed to confirm the condition [2]. Results from two earlier double-blinded placebo-controlled studies have given conflicting results. The first study showed that subjects who received gluten reported more gastrointestinal symptoms than those who received placebo [3]. The second study showed no specific or dose-dependent effect of gluten as compared to placebo after dietary reduction of fermentable, poorly absorbed short-chained carbohydrates (FODMAP) in subjects who were believed to have NCGS [4]. Subjects in these trials had coeliac disease excluded by negative HLA-DQ2/8 or normal duodenal biopsy while on a gluten-containing diet. Several double-blinded placebo-controlled gluten challenge trials have followed [5-7]. Recent trials suggest that gluten challenge induces symptom recurrence in only a minority of subjects who meet clinical criteria for NCGS [6]. Two other Italian trials aimed to discover true NCGS and found increased symptom score on gluten intake as compared to placebo, but only 5% and 14% were classified as NCGS according to predefined criteria [5,7]. In both studies gluten was administered as capsules.

89 88 Effects of gluten and fructans in gluten sensitivity All these trials have studied the role of gluten and used carbohydrate depleted gluten flour as the active challenge vehicle. However, people do not eat pure gluten flour. They report wheat as the symptom inducer. Considering the composition of wheat, where gluten co-exists with a substantial amount of FODMAP, in specific fructans, this component has not been taken into account in any challenge trial of NCGS [8]. The aim of the present study was therefore to investigate the effect of gluten and fructans separately in self-reported gluten-sensitive persons with muesli bars as challenge vehicle. Materials and methods Study design We describe a double-blind, placebo-controlled challenge study, where subjects were randomised to gluten, fructan and placebo challenges in a cross-over design (ClinicalTrials.gov, NCT ). The study took place at Oslo University Hospital, Rikshospitalet from October 2014 to May Figure 1. Study design. WO, wash out Subjects The study subjects were 59 adults (6 males) aged who self-reported gluten sensitivity, had been strictly adherent to a gluten-free diet (GFD) for at least six months followed by symptom relief and had no coeliac disease or wheat allergy. Coeliac disease was considered adequately excluded by negative duodenal biopsy while on gluten-containing diet or negative genotype HLA-DQ2/8. Wheat allergy was considered eliminated in case of negative wheat-specific IgE. Exclusion criteria were pregnancy or lactation, use of immunosuppressive agents, inflammatory bowel disease

90 5 Clinical research reports 89 or other comorbidity, substantial infection, long travel distance or allergy to nuts or sesame seeds. Subjects were recruited by advertisements on the Oslo University Hospital s web page, at the University of Oslo, at the web page of the Norwegian Coeliac Association and their social media, and by referrals from general practitioners and other hospitals in the area. Food challenge protocol The subjects were randomised to one of three challenges (gluten, fructan or placebo) for one week, followed by a minimum of one week washout period. They continued their GFD and were told to keep their diet otherwise consistent with the baseline diet throughout the study. The challenge vehicle was a 50 g, 220 kcal low-fodmap gluten-free muesli bar that was eaten once a day. The muesli bars were developed and produced by the Monash University, Melbourne. The fructan bar additionally contained 2.1 g of fructooligosaccharides and the gluten bar 5.7 g of gluten. The gluten used was commercially available, carbohydrate depleted wheat gluten (Vital Wheat Gluten, Manildra Group, Gladesville, New South Wales, Australia) with nutritional content of 75% protein, 9% carbohydrate of which 4% sugar, 6% fat, 9% water and 1% ash (Cargill analysis). The muesli bars were balanced in carbohydrates, fiber, fat and protein and had similar appearance, texture and taste, confirmed by pre-testing in 12 healthy adults where the gluten bar could not be differentiated from the fructan or placebo bar. Aim and outcome The aim was to investigate the effect of gluten and fructans separately in a doubleblind placebo controlled challenge in individuals with self-reported gluten sensitivity in absence of coeliac disease. The primary outcome was overall gastrointestinal symptoms measured by the Gastrointestinal Symptom Rating Scale irritable bowel syndrome version (GSRS-IBS). The secondary outcome was daily overall gastrointestinal symptom score by visual analogue scale (VAS) for abdominal pain, bloating, passage of wind, nausea, stool dissatisfaction and overall gastrointestinal symptoms. Results and discussion The manuscript is in preparation. Results will therefore not be presented here. References 1. Ludvigsson JF, Leffler DA, Bai JC, et al. The Oslo definitions for coeliac disease and related terms. Gut 2013; 62(1):

91 90 Effects of gluten and fructans in gluten sensitivity 2. Catassi C, Elli L, Bonaz B, et al. Diagnosis of non-celiac gluten sensitivity (NCGS): The Salerno experts' criteria. Nutrients 2015; 7(6): Biesiekierski JR, Newnham ED, Irving PM, et al. Gluten causes gastrointestinal symptoms in subjects without celiac disease: a double-blind randomized placebocontrolled trial. Am J Gastroenterol 2011; 106(3): ; quiz Biesiekierski JR, Peters SL, Newnham ED, et al. No effects of gluten in patients with self-reported non-celiac gluten sensitivity after dietary reduction of fermentable, poorly absorbed, short-chain carbohydrates. Gastroenterology 2013; 145(2): e Di Sabatino A, Volta U, Salvatore C, et al. Small amounts of gluten in subjects with suspected nonceliac gluten sensitivity: A randomized, double-blind, placebocontrolled, cross-over trial. Clin Gastroenterol Hepatol 2015; 13: e3. 6. Zanini B, Baschè R, Ferraresi A, et al. Randomised clinical study: gluten challenge induces symptom recurrence in only a minority of patients who meet clinical criteria for non-coeliac gluten sensitivity. Aliment Pharmacol Ther 2015; 42(8): Elli L, Tomba C, Branchi F, et al. Evidence for the presence of non-celiac gluten sensitivity in patients with functional gastrointestinal symptoms: Results from a multicenter randomized double-blind placebo-controlled gluten challenge. Nutrients 2016; 8(2): Biesiekierski JR, Rosella O, Rose R, et al. Quantification of fructans, galactooligosacharides and other short-chain carbohydrates in processed grains and cereals. J Hum Nutr Diet 2011; 24(2):

92 5 Clinical research reports Natural history and management of potential coeliac disease Renata Auricchio, Valentina Discepolo, Roberta Mandile, Maria Maglio, Luigi Greco, Riccardo Troncone Department of Medical Translational Sciences & European Laboratory for the Investigation of Food Induced Diseases, University Federico II, Naples, Italy Introduction According to the most recent European Society of Gastroenterology, Hepatology and Nutrition (ESPGHAN) guidelines, coeliac disease (CD) is considered an immunemediated systemic disorder elicited by gluten and related prolamins in genetically susceptible individuals [1]. Even if enteropathy remains the prominent feature of the disease, it is now widely accepted, that, from a histological point of view, it can range from complete villous atrophy to minimal mucosal abnormalities. In this context, the term potential coeliac disease (PCD) is used to define patients with normal or slightly altered intestinal mucosa (Marsh 0-1), but a positive CD serology. Patients with PCD may or may not have symptoms and may or may not develop an overt form of CD over time [2]. The number of patients with a diagnosis of PCD is increased so far because of the screening of general population and it is now estimated to be at the considerable number of 1/5-1/10 of the total CD diagnosis [3]. Clinical management of patients with potential coeliac disease Even if PCD patients do not show clear signs of enteropathy, some of them may present clinical symptoms. In our experience, abdominal pains and failure to thrive are the most frequent ones and are found in around 1/3 of symptomatic patients. Other symptoms are diarrhea (approximately 16% of patients), lack of appetite (13%), low blood ferritin (8%), vomiting and constipation (5%), anemia and hypertransaminasemia (3%). Biagi et al. have hypothesised that in PCD the intestinal mucosa is maintained architecturally normal thanks to an increased enterocytic proliferation, which, however, will end up in a reduced enterocytic maturity and thus in a reduced absorptive capacity of the small bowel [4]. There is a general consensus for this kind of patients to adopt a gluten-free diet (GFD) and to control, during the follow up, the remission of symptoms. On the contrary, the management of asymptomatic patients with PCD remains a major clinical problem. Some have suggested that, because this condition could be the first step of the disease, all patients should adopt a lifelong GFD. This was supported by the fact that an undiagnosed case of CD has a four-fold increased risk of mortality for all causes [5] and that the metabolic identikit of PCD patient is similar to the one of CD patients and differs from controls [6]. Moreover, despite per definition there is no clear

93 92 Natural history and management of potential coeliac disease villous atrophy in potential coeliac disease, in the last decade an increasing number of studies have suggested that mild signs of inflammation are often present. In fact, from an immunohistochemical point of view, 70.8% of PCD patients show increased numbers of lamina propria CD25+ and/or enhanced expression of ICAM-1 and crypt HLA-DR [7]. On the other hand, preliminary observations from our group demonstrated that most of the asymptomatic children with PCD remained healthy on a gluten-containing diet. During three years of follow up, CD-associated antibodies fluctuated (32.6%) or even disappeared (14.6%) and, after three years, only 30.8% of the patients developed villous atrophy [8]. Therefore, it would be an overtreatment to consider all PCD patients as coeliac. Unfortunately, we still have no good way to identify which subsets of seropositive patients will develop mucosal damage. Natural history of potential coeliac disease: a 9 years prospective longitudinal study The main challenge remains to find criteria that allow to differentiate, among PCD patients, those who will develop villous atrophy from those who will not. In order to study the long-term natural history of PCD disease and to explore risk factors associated with the development of mucosal atrophy, our group performed a 9 year prospective longitudinal study [9]. 175 asymptomatic children were left on a glutencontaining diet. Antibodies and clinical symptoms were checked every 6 months, and a small bowel biopsy was taken every 2 years to evaluate histological, immunohistochemical, and anti-tg2 deposits. Patients were genotyped for HLA and a set of non-hla CD-associated genes. At the end of the follow up, 67% of the patients still had a normal duodenal architecture (Fig. 1). Monitoring the individual profile of anti-tg2 antibodies, 43% of patients showed persistently elevated anti-tg2 level, 20% became negative during follow-up, and 37% showed a fluctuant anti-tg2 course with transiently negative values. Analysing the cumulative incidence of CD in relation to individual risk factors, we noticed that the anti-tg2 titer at the entry was not statistically different between those who remained potential and those who progressed (become atrophic or developed symptoms), but the variation of anti-tg2 correlated to the final outcome. In fact, none of the negative anti-tg2 patients developed full-blown disease, whereas among those who developed severe damage, 78.8% had persistently positive anti-tg2 compared with 43% of those who did not develop the intestinal damage. Up to date, the detection of intestinal deposits of immunoglobulin A (IgA) anti-tg2 by immunofluorescence was reported to be the best marker to identify, among patients with potential CD, those who will eventually develop a glutendependent enteropathy [8-10]. Moreover, to further explore which variable or risk factor is likely to differentiate the patients who progress to flat mucosa from those who do not, a multivariate analysis was performed: male sex, slight mucosal inflammation at time 0 (estimated by the numbers of CD25+ cells and γδ+ lymphocytes) and a certain genetic profile (genes HLA-DQ2 and polymorphism of IL12A, OLIG3, and IL2/IL21) may well start to delineate a cohort of individuals who are more prone to develop the disease.

94 5 Clinical research reports 93 Figure 1. Cumulative survival function in the cohort study. Percentage of cases who remained potential during follow-up [9] Conclusion Potential coeliac disease is a condition more and more frequently diagnosed because of the screening of the general population, however the clinical management of the disease remains debated. The presence of symptoms should always induce to prescribe a gluten-free diet. On the contrary, prescribing a gluten-free diet to all asymptomatic patients could be an overtreatment, as we demonstrated that only 33% of the patients will develop mucosal atrophy within 9 years. Unfortunately, there are still no biomarkers that can allow to differentiate with confidence patients that will develop an intestinal damage from those who will not. However, preliminary studies suggest that male sex, the number of CD25+ and γδ+ lymphocytes in the intestinal mucosa at the time of diagnosis, as well as HLA-DQ dose and some non-hla polymorphisms may help to identify a cohort of individuals more prone to develop overt disease. References 1. Husby S, Koletzko S, Korponay-Szabó IR, et al. European Society for Pediatric Gastroenterology, Hepatology, and Nutrition Guidelines for the Diagnosis of Coeliac Disease. J Pediatr Gastroenterol Nutr 2012; 54: Ludvigsson JF, Leffler DA, Bai J, et al. The Oslo definitions for coeliac disease and related terms. 2013; 62(1): Volta U, Caio G, Giancola, et al. Features and progression of potential celiac disease in adults. Clin Gastroenterol Hepatol 2016; 14(5): Biagi F, Trotta L, Alfano C, et al. Prevalence and natural history of potential celiac disease in adult patients. Scand J Gastroenterol 2013; 48(5): Rubio-Tapia A, Kyle RA, Kaplan EL. Increased prevalence and mortality in undiagnosed celiac disease. Gastroenterology 2009; 137:

95 94 Natural history and management of potential coeliac disease 6. Bernini P, Bertini I, Calabrò A, et al. Are patients with potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011; 10(2): Paparo F, Petrone E, Tosco A, et al. Clinical, HLA, and small bowel immunohistochemical features of children with positive serum antiendomysium antibodies and architecturally normal small intestinal mucosa. J Gastroenterol 2005; 100(10): Tosco A, Salvati VM, Auricchio R, et al. Natural history of potential celiac disease in children. Clin Gastroenterol Hepatol 2011; 9: Auricchio R, Tosco A, Piccolo E, et al. Potential celiac children: 9-year follow-up on a gluten-containing diet. Am J Gastroenterol 2014; 109(6): Korponay-Szabó IR, Halttunen T, Szalai Z, et al. In vivo targeting of intestinal and extraintestinal transglutaminase 2 by celiac autoantibodies. Gut 2004; 53:

96 5 Clinical research reports Association between IL-33/ST2 axis and active coeliac disease Federico Perez 1, David Diaz Jimenez 2, Carolina N. Ruera 1, Marjorie de la Fuente 2, Glauben Landskron 2, Agustina Redondo 4, Luciana Guzman 3, Marcela Hermoso 2, Fernando Chirdo 1 1 Instituto de Estudios Inmunológicos y Fisiopatológicos, Facultad de Ciencias Exactas, Universidad Nacional de la Plata, Argentina 2 Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile 3 Servicio de Gastroenterología Hospital de Niños "Sor María Ludovica" de La Plata, Argentina 4 Servicio de Gastroenterología HIGA San Martin, La Plata, Argentina Introduction IL-33, a member of the IL-1 family, is mainly expressed by epithelial, endothelial and mesenchymal cells [1]. In resting cells, it is located principally in the nucleus, where it can regulate the expression of certain genes by its interaction with different transcriptional factors. It has been proven that this protein can be released from the nucleus into the cytoplasm and then to the extracellular space by different kinds of stimuli inducing a strong inflammatory response through its receptor, ST2. The IL-33 receptor is a heterodimeric complex made up of two different proteins ST2L, which actually binds IL-33 and an accessory protein known as IL-1RAc. This receptor is expressed by different cells: lymphocytes, mast cells, NK cells, ILC2, and endothelial, epithelial and mesenchymal cells. The ST2L protein has a splice variant, named as soluble ST2 (sst2) which can be released into the extracellular space where it works as decoy factor for IL-33 [2-3]. Since the discovery of IL-33 many different functions have been linked to this cytokine. Firstly, it was recognised for its capacity to promote Th2 responses [4]. More recently, it has been shown that IL-33 may also promote Th1 functions [5]. It is clear that IL-33 acts not only as a cytokine, but also as alarm signal, stimulating many proinflammatory responses [6]. Particularly, necrotic cells, but not apoptotic ones, release an active form of IL-33 with potent biological effects [2]. Based on the functional properties of this molecule, we aimed to investigate whether IL-33 may play a role in coeliac disease (CD) pathogenesis. It has been recently observed that CD patients present increased levels of IL-33 [2]. In the present work, we evaluate the expression of IL-33 and its receptor in human intestinal mucosa. These are the initial studies in order to link the biology of IL-33 and the mechanisms of CD pathogenesis.

97 96 Association between IL-33/ST2 axis and active coeliac disease Materials and methods Blood samples from a total of 40 untreated CD patients and 39 healthy controls were evaluated in this study. Duodenal biopsies from 9 untreated CD patients and 9 healthy controls were used to perform immunofluorescence assays. All the samples were taken during the routine protocol for CD diagnosis in the Gastroenterology Units of Hospital Sor María Ludovica (paediatric patients) and Hospital San Martin (adult patients). The study was approved by the ethics committee of both institutions. For immunofluorescence analysis, 4 µm sections of duodenal paraffin-embedded tissues were used. Antigen retrieval was performed by heat treatment in citrate buffer, and stained with commercial antibodies from R&D systems (AF3625 for IL-33 and AF523 for ST2). Nuclei were stained with DAPI. Images were obtained using a SP5 Leica confocal microscope. The cellular density was calculated as the number of positive cells for each marker in a predefined zone. Levels of ST2 and IL-33 in serum samples were determined by commercial ELISA kits (R&D System, cat. DY523 for ST2, and ab for IL-33). Comparison of the expression levels for IL-33 and ST2 in serum and positive cell numbers in lamina propria between control subjects and active CD patients was performed using unpaired T-tests with 95% of confidence. Results and discussion First, we determined the concentration of circulating IL-33 and the soluble form of ST2 (sst2) in untreated CD patients and healthy controls by commercial ELISA. Increased levels of sst2 in sera of untreated CD patients were observed. The mean ** 600 * ST2 pg/ml IL-33 pg/ml Celiacs Controls Celiacs Controls Figure 1. Concentration of IL-33 and its decoy receptor (sst2) in serum samples of untreated CD patients (n=37 for sst2 and 21 for IL-33) and healthy controls (n=39 for sst2 and 9 for IL-33). Plots show the mean value plus SEM bars of the concentration of IL-33 and sst2 (pg/ml). (IL-33, *p<0.01, sst2: ** p<0.005) 0

98 5 Clinical research reports 97 value of sst2 was 264,1 pg/ml for untreated CD patients while 96.5 pg/ml was observed for healthy controls (Fig. 1). Untreated CD patients presented also increased levels of IL-33. The mean value for CD patients was pg/ml and pg/ml for healthy controls. Next, we aimed to evaluate the expression of IL-33 and ST2 in the intestinal mucosa. To this end, we evaluated sections of duodenal biopsies from untreated CD patients and healthy controls by immunofluorescence. The immunofluorescence images showed a higher number of IL-33 and ST2 expressing cells in the lamina propria of active CD patients than in controls. The epithelium showed a faint staining. However, in some CD patients some cells from the epithelial compartment showed a strong staining for both proteins. The ST2 + cells were located close to the epithelium. IL-33 + cells did not appear randomly distributed. On the contrary, they seem to be organised or associated with some structures resembling blood vessels. In order to quantify the number of IL-33 + or ST2 + cells located in the lamina propria, we performed manual counting of each group of cells. Cells were counted per m 2 of lamina propria to obtain the density of positive cells. Higher numbers of IL-33 + and ST2 + cells were observed in duodenal lamina propria from untreated CD patients (Fig. 2). Number of ST2+ cells ** Celiacs Controls Figure 2. Increased numbers of IL-33 + cells and ST2 + cells in duodenal lamina propria from untreated CD patients. Counting of IL-33 + cells and ST2 + cells in immunofluorescence images of predefined areas of duodenal lamina propria of untreated CD patients (n=9) and healthy controls (n=9). Plots show the mean value plus SEM bars of the number of IL-33 + cells and ST2 + cells per m 2 of lamina propria, (ST2 ** p<0.05, IL-33 * p<0.1) Since CD is a very well-known Th1 driven enteropathy [8], the high expression of IL- 33 in duodenal mucosa and in peripheral blood of untreated CD patients is intriguing. Number of IL-33+ cells Celiacs * Controls

99 98 Association between IL-33/ST2 axis and active coeliac disease Recent works have demonstrated the broad spectrum of effects of IL-33 in different pathologies. Yang et al. proved that only cytotoxic T cells in a context Th1 or Th17 express ST2 [9]. These authors also confirmed that IL-33 synergises with IL-12 to induce effector cells. In addition, other studies confirmed that IL-33 and ST2 expression was necessary to mount a cytotoxic response against some virus infections and tumours, highlighting the role of the IL-33/ST2 axis in the induction of potent cytotoxic T cells [10-11]. Bourgeois et al. showed that IL-33 directly interacts with inkt and NK cells to induce IFN-γ production [12]. On the other hand, IL-33 enhanced Th1/Th17 responses in some mouse models [13-14]. Therefore, we hypothesise that the IL-33/ST2 axis may have a role in CD pathogenesis, probably expanding the inflammatory process, and promoting a Th1 and cytotoxic response. Further work is in progress to investigate the signal involved in the up-regulation of this factor and also the consequences of its systemic release. Conclusion In this study, we found higher levels of IL-33 and sst2 in serum of untreated CD patients compared with healthy controls, together with an increase in the number of IL-33 + and ST2 + cells in duodenal lamina propria of untreated CD patients. Since IL-33 is mainly located in the nucleus of different cells, upregulation of IL-33 expression points to its role as alarm signal. Though the test used to evaluate serum IL-33 levels does not discriminate active and inactive form, it is likely that part of the circulating IL-33, released from the intestinal mucosa, may reach distant tissues initiating a tissue damage process. IL-33 together with other cytokines, such as IFN- and IL-15 may also be part of the inflammatory mediators which link CD to other inflammatory/autoimmune diseases such as type I diabetes and rheumatoid arthritis. References 1. Moussion C, Ortega N, Girard JP. The IL-1-like cytokine IL-33 is constitutively expressed in the nucleus of endothelial cells and epithelial cells in vivo: A novel Alarmin? PLoS One 2008; 3(10): Martin MU. Special aspects of interleukin-33 and the IL-33 receptor complex. Semin Immunol Elsevier Ltd 2013; 25(6): Martin NT, Martin MU. Interleukin 33 is a guardian of barriers and a local alarmin. Nat Immunol Nature Publishing Group 2016; 17(2): Schmitz J, Owyang A, McClanahan TK, et al. IL-33, an interleukin-1-like cytokine that signals via the IL-1 receptor-related protein ST2 and induces T helper type 2-associated cytokines. Immunity 2005; 23(5):

100 5 Clinical research reports Baumann C, Bonilla WV., Hegazy AN, et al. T-bet and STAT4 dependent IL-33 receptor expression directly promotes antiviral Th1 cell responses. Proc Natl Acad Sci 2015 Mar 31; 112(13): Haraldsen G, Balogh J, Sponheim J, et al. Interleukin-33 cytokine of dual function or novel alarmin? Trends Immunol 2009; 30(5): López-Casado M, Lorite P, Palomeque T, et al. Potential role of the IL-33/ST2 axis in celiac disease. Cell Mol Immunol 2017; 14: Nilsen EM, Jahnsen FL, Sollid LM, et al. Gluten induces an intestinal cytokine response strongly dominated by interferon gamma in patients with celiac disease. Gastroenterology 1998; 115(3): Yang Q, Li G, Zhu Y, et al. IL-33 synergizes with TCR and IL-12 signaling to promote the effector function of CD8+ T cells. Eur J Immunol 2011; 41(11): Bonilla WV, Frohlich A, Johnson S, et al. The alarmin interleukin-33 drives protective antiviral CD8+ T cell responses. Science 2012; 335(6071): Gao X, Wang X, Li G, et al. Tumoral expression of IL-33 inhibits tumor growth and modifies the tumor microenvironment through CD8+ T and NK cells. J Immunol 2014; 194(1): Bourgeois E, Van LP, Samson M, et al. The pro-th2 cytokine IL-33 directly interacts with invariant NKT and NK cells to induce IFN-γ production. Eur J Immunol 2009; 39(4): Palmer G, Seemayer CA, Viatte S, et al. Inhibition of interleukin-33 signaling attenuates the severity of experimental arthritis. Arthritis Rheum 2009; 60(3): Xu D, Jiang H-R, Fraser AR, et al. IL-33 exacerbates antigen-induced arthritis by activating mast cells. Proc Natl Acad Sci U S A. 2008; 105(31):

101 100 Association between IL-33/ST2 axis and active coeliac disease

102 5 Clinical research reports Abrogation of coeliac immunogenicity of gluten peptides by amino acid point substitutions Nika Japelj 1, Beatriz Côrtez-Real 1, Tanja Šuligoj 1, Wei Zhang 2, Joachim Messing 2, Uma Selvarajah 1, Paul J. Ciclitira 1 1 Department of Gastroenterology, Kings College, St Thomas Hospital, London, United Kingdom 2 Rutgers University, Waksman Institute of Microbiology, New Jersey, USA Introduction The only generally accepted treatment of coeliac disease (CD) is a life-long gluten-free diet. Wheat gluten proteins include gliadin, low- (LMWG) and high-molecular-weight glutenins (HMWG), all three of which have shown to be CD-toxic [1,2,3]. A glutenfree diet significantly reduces the quality of life for affected individuals such that new approaches are sought. We have identified naturally existing variants of gliadins and glutenins that might be less immunotoxic in CD [4]. Aims We sought to test selected variants of α-gliadin peptides in CD T-cell proliferation assays with gluten-sensitive T-cell lines that had been generated from duodenal biopsies from individuals with CD. This would allow us to evaluate their CD-toxic immunogenicity. We sought to identify peptides with lower CD-toxic immunogenicity as a prelude to providing the basis of new dietary strategies as part of a gluten-free diet for individuals with CD. Materials and methods We generated gluten-specific polyclonal T-cell lines from duodenal biopsies taken from individuals with CD (n=11) as previously described [5] although not all the T- cell lines were used in every study. The candidate peptides, as shown in Fig. 1, were tested in proliferation assays using radioactive labelled thymidine to measure T-cell proliferation. A stimulation index >2 was considered positive. We tested five α-gliadin peptides synthesised as 16mers. The results of proliferation T-cell assays with medium alone, PT digested gluten, peptides 1, 3, 5, 6, and 9 are presented in Tab. 1. The set of tested peptides harbored the overlapping T-cell epitopes DQ2.5-glia-α-1a and DQ2.5- glia-α-2, and naturally occurring variants that differed in a few amino acids (shown in Fig. 1).

103 102 Amino acid point substitutions and coeliac immunogenicity of gluten peptides Table 1: Results of 11 proliferation assays: 11 gluten-sensitive T-cell lines were tested with medium only, peptic tryptic digested gluten and peptides 1, 3, 5, 6 and 9. Stimulation indices for individual antigens are marked in bold and corresponding arithmetic mean ± standard deviation in brackets. Note that SI greater than 2 were considered as positive.

104 5 Clinical research reports 103 Results and discussion Approximately half of gluten-specific cell lines (5:10) recognise immune-dominant peptide 1 (QLQPFPQPQLPYPQPQ) or its deamidated counterpart (QLQPFPQPELPYPQPQ, peptide 3). Stimulation indices vary from That confirms different sensitivity of T cells obtained from different patients to particular epitopes. Notably, indices increase when peptide 1 is deamidated (Fig. 2). Peptide 3 s point substituted variant (QLQPFPQPELSYPQPE, Peptide 5) triggered positive T-cell responses in 2:6 CD gluten-sensitive T-cell lines, the results of which are shown in Fig. 3. Peptides with two substitutions (QLQPFQPKLSYPQPE, Peptide 6) or three amino acid substitutions (QLQPFPKPKPKLPYPKPQ, Peptide 9) did not stimulate any tested gluten-sensitive T-cell lines (n=8 and n=5, respectively). The above results indicate the importance of both deamidated glutamic acid (at position 65, Fig. 1) and proline (at position 67, Fig. 1) in triggering coeliac-specific reactions. Conclusion We have shown that introduction of two selected amino acid substitutions in α-gliadin peptides abrogates responses of CD gluten-sensitive T cells to these peptides. We suggest that these peptides will need additional assessment using CD small intestinal biopsy organ culture and in vivo testing to confirm their lack of CD toxicity. Peptide Sequence Substitutions Peptide 1 Q L Q P F P Q P Q L P Y P Q P Q Peptide 3 Q L Q P F P Q P E L P Y P Q P E deamidated Peptide 5 Q L Q P F P Q P E L S Y P Q P E S67 Peptide 6 Q L Q P F P Q P K L S Y P Q P E K65, S67 Peptide 9 Q L Q P F P K P K L P Y P K P E K63, K65, K70 Epitope DQ2.5- glia-α1a positions Epitope DQ2.5- glia-α2 positions p1 p2 p3 p4 p5 p6 p7 p8 p9 p1 p2 p3 p4 p5 p6 p7 p8 p9 Figure 1. Amino acid sequences for α-gliadin peptides and substituted variants used in the study. Letters in bold indicate amino acid substitutions within the immunodominant p57-72 α-gliadin peptide. The bottom part of the table shows epitopes within this peptide and the position of their binding into the HLA-DQ2 groove (p1-9)

105 104 Amino acid point substitutions and coeliac immunogenicity of gluten peptides Peptide 1 patient K patient J patient I patient H patient G patient F patient E patient D Peptide 3 patient C patient B Stimulation index (SI) patient A Figure 2. Proliferative response of T-cell lines to immunodominant peptide 1 (epitope DQ2.5-glia-α1a positions and DQ2.5-glia-α2) and to deamidated counterpart Peptide 3 patient K patient J Peptide 5 patient I patient H patient G Peptide 6 patient F Patient E Patient D Patient C Peptide 9 Patient B Patient A Stimulation index (SI) Figure 3. Proliferative response of T-cell lines to different α-gliadin peptides; peptide 3, peptide 5, peptide 6 and peptide 9. With every further peptide, one amino acid substitution is introduced. With 2 amino acid substitutions, T-cell response is completely abrogated

106 5 Clinical research reports 105 References 1. Ciclitira PJ, Evans DJ, Fagg NL, et al. Clinical testing of gliadin fraction in coeliac patients. Clin Sci 1984; 66: Vader W, Kooy Y, van Veelen P, et al. The gluten response in children with coeliac disease is directed towards multiple gliadin and glutenin peptides. Gastroenterology 2002; 122: Dewar DH, Amato M, Ellis HJ, et al. The toxicity of high molecular weight glutenin subunits of wheat to patients with coeliac disease. Eur J Gastroenterol 2006; 18: Zhang W, Ciclitira PJ, Messing J. PacBio sequencing of gene families A case study with wheat gluten genes. Gene 2014; 533:(2) Molberg O, McAdams S, Lundin KE, et al. T cells from coeliac disease lesions recognize gliadin epitopes deamidated in situ by endogenous tissue transglutaminase. Eur J Immunol 2001; 31:

107 106 Amino acid point substitutions and coeliac immunogenicity of gluten peptides

108 5 Clinical research reports Estimation of (sero) prevalence of coeliac disease in children and adolescents in the LIFE Child study cohort Johannes Wolf 1, Norman Haendel 2, Anne Jurkutat 3, Carl Elias Kutzner 1, Gunter Flemming 2, Wieland Kiess 2,3, Andreas Hiemisch 2,3, Antje Körner 2,3, Wolfgang Schlumberger 4, Joachim Thiery 1,3, Thomas Mothes 1 1 Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, Medical Faculty of the University and University Hospital, Leipzig, Germany 2 Department of Women and Child Health, Hospital for Children and Adolescents and Centre for Paediatric Research (CPL), University of Leipzig, Germany 3 LIFE Leipzig Research Centre for Civilization Diseases, University of Leipzig, Germany 4 EUROIMMUN Medizinische Labordiagnostika AG, Lübeck/Dassow, Germany Introduction The prevalence of coeliac disease (CD) in population-representative cohorts is reported between 0.18 and 2.38% [1] depending on the size and mean age of the screened population as well as on the applied serological tests. Currently, four studies are available estimating the frequency of CD in Germany [1-4] which screened in different cohorts (paediatric and/or adult cohorts) and applied varying screening strategies. The prevalence of biopsy-proven CD was found between 0.18 and 0.37% [1,2]. This seems to be underestimated considering the frequency of CD in other European countries [5]. Contrary, seroprevalences in randomly selected cohorts were found between 0.8 and 1.35% [3,4]. This suggests a higher frequency of CD in Germany but might be due to a certain low degree of unspecificity of the applied antibody tests. Otherwise, a recent screening [6] demonstrated that 98% of the participants with IgA anti-tissue transglutaminase (IgA-aTTG) values 10 times of upper limit (ULN) exhibit mucosal impairment compatible with CD ( Marsh 3A). The primary objective of our ongoing study was to estimate (sero)prevalences in a paediatric randomly selected German cohort by applying additionall confirmatory antibody tests and HLA genotyping. Furthermore, we asked the question if antibody test results alone can predict the actual prevalence of CD in a paediatric cohort. Materials and methods Study population The Leipzig Research Centre for Civilization Diseases (LIFE) Child study has been designed to understand how and through which mechanisms and mediators genetic,

109 108 Prevalence of coeliac disease in children and adolescents metabolic and environmental factors influence health and development in children and adolescents [7]. LIFE Child is a prospective, longitudinal population-based cohort study of urban children from fetal life until adulthood. The study focuses on monitoring of normal growth, development and health non-communicable diseases such as childhood obesity, atopy and mental health problems. Families were randomly selected and invited by the residents registration office. Between 2011 and 2015, 3080 children and adolescents were included, of whom 2363 participants were enrolled for our CD screening due to the inclusion criteria (age between 1 and 18 years, at least two serum aliquots of the first visit with blood withdrawal available). Study procedure The study procedure is shown in Fig. 1. We performed a four-step CD screening. The first step comprised determination of IgA-aTTG and IgG-antibodies against deamidated gliadins (IgG-aDGL) in sera (T0) using tests of EUROIMMUN AG (Lübeck, Germany). Afterwards, samples with positive results for IgA-aTTG (including also samples with IgA-aTTG values between 0.5 and 1 x ULN) and for Figure 1. Study procedure. CD coeliac disease, EmA endomysium antibodies, GFD gluten-free diet, IgA-aTTG IgA anti-tissue transglutaminase, IgG-aDGL IgGantibodies against deamidated gliadins, JIRA juvenile idiopathic rheumatoid arthritis, T1 follow-up in LIFE Child, T1DM diabetes mellitus type I, T2 personal interview, ULN upper limit of normal

110 5 Clinical research reports 109 IgG-aDGL or samples of patients with CD-associated disorders as well as known CD were tested for endomysium antibodies (EmA) and HLA-DQ2 (HLA-DQ2.5 and/or DQ2.2) and -DQ8 using tests of EUROIMMUN AG (Lübeck, Germany). In sera only positive for IgG-aDGL, total IgA was nephelometrically measured (Roche, Mannheim, Germany). IgA values of 0.05 g/l were considered as sign of selective IgA deficiency (sigad). In a third step, available follow-up sera (T1) of patients with conspicuous results for IgA-aTTG and/or IgG-aDGL (HLA-DQ2 and/or DQ8 positive or HLA status not known) were analysed for IgA-aTTG, IgG-aDGL and EmA. Finally, we invited participants (T2) who showed positivity for either IgA-aTTG and/or IgG-aDGL at T0 and T1. Cases with negative HLA results were not pursued. The final step included a personal interview which comprises questions concerning gastrointestinal complaints and further CD-relevant symptoms, associated diseases, family history and gluten uptake as well as the decision of the participant for further clarification. The interview was performed by an experienced paediatric gastroenterologist. The latter is still ongoing. Interim analysis To compare our data with other screening studies, the following groups were considered: Known CD (group 1): known CD with HLA-DQ2/DQ8 positivity. Seropositivity (group 2): IgA-aTTG >1 x ULN or (IgG-aDGL >1 x ULN and sigad) + group 1. Potential CD (group 3): (IgA-aTTG >1 x ULN and IgA-EmA-positive) or (IgGaDGL >1 x ULN and sigad and HLA-positive) + group 1. Probable CD (group 4): IgA-aTTG 10 x ULN and IgA-EmA-positive + group 1. Results and discussion Characteristics of our screening cohort are shown in Table 1. Results regarding the first two steps of our screening procedure are depicted in Fig. 2. Of 2363 children and adolescents, 29 were only positive for IgA-aTTG (1.23%) and 23 only for IgG-aDGL (0.87%). The results for IgA-aTTG are comparable with a previous observation in an adult cohort [3]. Double positivity for the indicated antibodies was observed for 11 patients (0.47%, not shown). Of seven participants who noted that CD was previously diagnosed, one was positive for IgA-aTTG (probable under GFD) but only four (including the indicated patient) were HLA-DQ2 and/or DQ8 positive. We conclude that inclusion of probands indicating to have CD into the calculation of prevalence without HLA-typing [4] leads to an overestimation of frequency.

111 110 Prevalence of coeliac disease in children and adolescents Table 1. Baseline demographics and clinical characteristics. Probands included for analysis 2363 Gender (female in %) 49.0 Age in years (mean) 8.5 Probands with known CD (according to LIFE interview) 7 Cases of suspected CD 2 Children with diabetes mellitus type 1 6 Children with autoimmune thyreoiditis 4 Children with juvenile idiopathic arthritis 4 Data were obtained by LIFE child questionnaire Figure 2. Screening results regarding IgA-aTTG, IgG-aDGL, IgA-EmA and HLA-type. HLA+ HLA-DQ2 and/or DQ8 positive, IgA-EmA+ IgA-EmA positive, sigad selective IgA deficiency, ULN upper limit of normal None of the participants with solely IgG-aDGL positivity was positive for IgA-EmA. Otherwise, all participants with IgA-aTTG 5 x ULN were also positive for the immunofluorescence test. In the group of probands with IgA-aTTG between 1 and 5 x ULN, there were only eight of 13 sera in which IgA-EmA were detected. Further, none of the sixteen patients (0.67%) with IgA-aTTG between 0.5 and 1 x ULN show IgA- EmA positivity. These findings contradict the observations of a large Swedish screening study in which 25% of the IgA-TTG negative probands (between 0.5 and 1 x